{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Author: Sebastian Raschka\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.8.8\n",
      "IPython version      : 8.2.0\n",
      "\n",
      "torch: 1.11.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a 'Sebastian Raschka' -v -p torch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Runs on CPU or GPU (if available)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Convolutional Neural Network on MNIST"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import time\n",
    "\n",
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    torch.backends.cudnn.deterministic = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "##########################\n",
    "### SETTINGS\n",
    "##########################\n",
    "\n",
    "# Device\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "# Hyperparameters\n",
    "random_seed = 1\n",
    "learning_rate = 0.001\n",
    "num_epochs = 10\n",
    "batch_size = 128\n",
    "\n",
    "# Architecture\n",
    "num_classes = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install gitpython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "from git import Repo\n",
    "\n",
    "if not os.path.exists(\"mnist-pngs\"):\n",
    "    Repo.clone_from(\"https://github.com/rasbt/mnist-pngs\", \"mnist-pngs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision import transforms\n",
    "\n",
    "data_transforms = {\n",
    "    \"train\": transforms.Compose(\n",
    "        [\n",
    "            transforms.Resize(32),\n",
    "            transforms.RandomCrop((28, 28)),\n",
    "            transforms.ToTensor(),\n",
    "            # normalize images to [-1, 1] range\n",
    "            transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),\n",
    "        ]\n",
    "    ),\n",
    "    \"test\": transforms.Compose(\n",
    "        [\n",
    "            transforms.Resize(32),\n",
    "            transforms.CenterCrop((28, 28)),\n",
    "            transforms.ToTensor(),\n",
    "            # normalize images to [-1, 1] range\n",
    "            transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),\n",
    "        ]\n",
    "    ),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data.dataset import random_split\n",
    "from torchvision.datasets import ImageFolder\n",
    "\n",
    "train_dset = ImageFolder(root=\"mnist-pngs/train\", transform=data_transforms[\"train\"])\n",
    "\n",
    "train_dset, valid_dset = random_split(train_dset, lengths=[55000, 5000])\n",
    "\n",
    "test_dset = ImageFolder(root=\"mnist-pngs/test\", transform=data_transforms[\"test\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "\n",
    "train_loader = DataLoader(\n",
    "    dataset=train_dset,\n",
    "    batch_size=batch_size,\n",
    "    drop_last=True,\n",
    "    num_workers=4,\n",
    "    shuffle=True,\n",
    ")\n",
    "\n",
    "valid_loader = DataLoader(\n",
    "    dataset=valid_dset,\n",
    "    batch_size=batch_size,\n",
    "    drop_last=False,\n",
    "    num_workers=4,\n",
    "    shuffle=False,\n",
    ")\n",
    "\n",
    "test_loader = DataLoader(\n",
    "    dataset=test_dset,\n",
    "    batch_size=batch_size,\n",
    "    drop_last=False,\n",
    "    num_workers=4,\n",
    "    shuffle=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RJC87EonAaDQik8lwekoQBEilUnQ6Hd6A9D2VSgW1Wg25XA6VSgWHw4FCocAU7pOGSqXC3NwcZmdncf36dczMzMDj8UAul6Pb7SKTySCTyeBXv/oVL+ZqtYp6vQ6ZTAalUolLly7B5XLhlVdegcVigdvtfqyR63a7SCQSyGazaDQaJ+p5U3uHXC6HQqFAp9PhVEy/3+eapV6v5xoRXS/9n8lkgkqlgl6v5+8R41IccdXrdU43kiPUaDQ4FXeaoDQgfbZKpRIzMzNotVpIJpPo9XrM1D0voPaGcDiMv/f3/h4WFhYwPT3N2Yqj2YejP0ug9RyPx7GysoKHDx9ie3sbm5ubKJfLYxLGC6BUKiEej+P+/ftIpVKIxWIAvmoBq1ar2NzcRDqdxsbGBmq1GorFIrrdLlqtFqRSKTQaDZNogEfM+Xw+j2q1OlaZeg6cuRGk5l06KMUPjw5Lom2XSiWOAk0mE5RKJTeaEtX4cWSakwBFcSaTCVarFQaDAWq1mj3marWKXC6H1dVVVCoVTl0QvVmhUECr1aLZbCIQCEAQBNhstkMeOn0G/X4ftVoNzWYTvV7v2Dw8MrjUFkC1H6q5qlQq7kdSKpXo9Xp87SaTiSnd9HtI8YL6mkwmE7eF0HOh50t1J4lEgk6ng1arxYdyo9E4dSMoNs50LyaTCQ6Hg9OHYlGDUQc9J5vNBq/Xi8nJSfh8PthsNq49UX1Z/Fk/7v6azSaSyST29vawubmJSCSCWCyGcrmMZrN5ruulZ4Vms8lRHRGRDg4O0Ol0+LxYX19HJpNBOp1Gq9VCq9Xi50XnnkKhgEKhgCAI/PO9Xm/8PJ4DZ2YEKe1itVpht9vx9//+38fMzAymp6eh0WigUCjY+97c3EQmk8Hnn3+O4XAIjUaDq1ev4o033uDD+saNGzCZTPj44495IZ0kJBIJNBoNdDodR0UKhQKNRgPNZhPxeBybm5v45JNPUKvV0G63+bCgQ7ZSqcDpdEIqlWJmZgZ6vR5msxkGgwHAV0XxRqOBbDaLYrHI5JiXBdUZlUolFhYWYLPZ4PP5oNVqYbPZuDG60+mg2+1ydEaGTq/Xs7QTGUFyaEjhQqvVQiqVcipXnPIdDAYcZdXrdVQqFdy6dQtbW1uoVCpnkn4kQ0gRFPVeUQrxPIDWlsPhgN/vx5/92Z8hFArh8uXL/MxkMhkODg4QjUZRrVYRj8efqr5UKpVw69YtZDIZ7O3toVwu85oep9xeDOl0GtVqlbNXVAIijkSn02ExDWpXORrdkeMql8sBPEqjUt/0OBJ8dpyZEaQD2OfzwePxYGJiAl6vl1OcgiBwamx/fx+pVAq7u7ussuDz+VCpVGAymZj1RoSUp6V5jgti1tZgMOB8PkU55Lk1m83H9lENBgM0Gg3U63Wm4R+VrTo4OODUCLFDX6b+QgckUeV1Oh10Oh2mpqbgdDoRDAah0WhgsVi45koKIo1GA4PBgNOapCCi0Wi+FlGIo3G6p4ODA0gkEk61UgQolUpRLBYBgMURTpv487j6syAI0Gg0MBgMfL2jDqpTq1Qq+Hw+BINBTE1Nwe12syGXSqVot9totVpIJBIoFArY3d09JLl1dH1VKhVEIhGUSiUUi0Vez6fJUiYniu6B6u7EKSDBjOFweMjpos/lKPFHHPFTtkLsBNEXGZZOp3OsDFjqaSaHSy6X8z4hQ9ZoNNDtdh+75+mcIflIehb0s8cBcoipdeMoqF+ZJB0pMBC3hL0MKLLtdDooFotoNpuo1+sv9TsfhzMxgoIgwGw2w2q14r333sPk5CTeeustJonQhxePxxGNRvHRRx8hFotheXkZCoUCbrcbJpMJfr8fs7OzsNvtrLl5WkaQxGuLxSJqtRobOaorkYGjeuZR0AKiFGmv1zsUKQ2HQ/R6PUSjUUQiEeRyOVSr1ZdSg5BIJNDpdLBarfD5fHC73bDb7Xj99dfh9XoRDAa5sV/MCCSSj/iAoHRar9fjVC1FqvV6/ZC6Pd2/VCrF0tISG2CJRAKfz4e9vT20Wi0+CM7Cg6UDSHygmEwm7pU7C+P8PCDnxOFwwGq14t1338XU1BRef/11aDQajmSHwyFSqRSy2Sw+/vhjpFIprK6usjP3uM++1Wphf3//VFjXTwJlJtxuN7ezdLtdNJtNroOVy2X0+30m/qjV6kN6qRKJhKOmdrvNtW2Sk6O1Ln5tt9tFsVhEMpnE/v7+sd1Pu91Gu91GrVZ7oZ/v9/u816hePxwOUavV0Gq1jmUP+f1+/OhHP8KlS5cwPz9/6FwlI7y/v487d+5wUDM5OQmz2QyTyfRSZSnai4lEAslkEh999BF2d3exvLz80vd1FKduBCl96Xa74fV6MTMzg1AoxBp6pIvXaDQQjUaxubmJvb09pFIpVKtVaDQa9uLEBu+0DyiK0oj9SQc95erVajXUajWndcWHh0KhgFwuh9vthtvtRigUgsfjYSIJEVHq9To2Njawvb3N9ZcXjQQp+iNdwoWFBdZpnZqagtlsPtTYPxgM2AvrdrvodDqHUl+CIKDT6aDRaKBYLKJarbKMlngTklEjMYBQKMRe5WAwQLfbRaFQQDQaRSaTQalUOpN6IB2odC/NZpMjK4qY6QAdpRQgrTdxVO9yuTA7Owu/33+oHYIO3mg0ilgshq2tLWSzWSSTSU6HPg4UCZ1VfyoJSphMJly6dAlGoxEul4vLJeSIlkol9Ho9dlqo6VwcGdIzpCyEVqvlLBJFlnR4C4KAer2Ovb29kdEnJlBGh6bOiJ244+QMSKVSHgAgbuIHHu0DOisoc+TxeHgtvkwwQkZWoVBAr9ejWq1CrVbzc67Vase2Hs/ECBqNRk7VXLhwAX6/H2az+RAxIpVKYWNjAw8ePMDm5iYKhQIqlQqTEyg1clZpqsFggEqlgkqlwoQV4Ks8vUajgVarhUqlOiR4TbU4jUaDcDgMv9+Pubk5BINBmEwmPnCKxSLy+Tzu3buHSCSCQqGARqPxQg+eDnOj0YhQKIS5uTm89dZb8Pl8cDqd3NYhbs4no0Cp2Fqtxukm+iIDmE6nUSgUEIvF2HjTdZIX7nA4YLPZcPXqVZaDIwJRKpXC+vo69vf3kcvlTr3vbDgcotPpoFarce21Xq+zaIPRaOQ6J0XFowJiSttsNjgcDiwtLcHv9+Py5cuw2WyH9kiz2USpVMLGxga2trawsrKCQqHAAu6jXEMiPd0333wTVqsVbrcb/X4f3W6XHcRischG8OjoIXHNWhAEdLtd/uyIaS6u2QOPjH8+n+fm81EBkQNVKhU7l8BXWajjrAnSeaXX62GxWA7VxofDIRMD6bM1GAyHyDovg4ODA5jNZrhcLhZVqVarWF9fR6PROLZ7PDUjSIoVDocDoVAIFy9exNzcHNcrBEFgcdhoNIovvvgC9+/fx8bGBheIyfgR6cJkMkEul6Pf7yMej2N/f//UZmodHByg2WyiVquhUCigXC5z+4NOp4Pf70e328X09DQymQwSiQTXHgKBAGw2G95//334/X5cvHgRWq0W7XYb5XIZ5XIZd+/eRTwex+eff45MJsOK/S8CqVQKp9MJr9eL119/HZOTk1haWmKJJjpM6LMjYlEul0MsFkMmk0EqlTrEBCQhAHHNktIyxF6jPkq73Q6fz4dQKASr1QqNRoNut4tSqYQHDx5geXkZGxsbTBY4bSNzlICUSqUQj8fh9/tZlIEEpI/Ofzwr0EFoMBjgdrsxPT2NyclJXL16FW63G06nk/VqCWToW60WR/ajzuwUawtPTk7iypUrnLWgyIdqgrQ+KZshPoiPGjhxTZCiKHJWqeZZLpdRKpVQKpXQarXO8mNgUIRLIttzc3MIhULodDqoVquoVCrHlg6tVCpYXV3FwcEBkskkyzvq9Xre21QeobVE6V1S76pUKny2iBW0qBx0dP1R4EARpdVqhV6vh8fjQTabhd1ux/7+PpdqjgOnagTpg/N4PAgGgwiHwxxmU2TQbDaRyWSwsbHBaVBxbxylQUnYl5pC8/k8crncE2twxw06OFutFjf61+t1bt2wWq2o1+sIBAIAHjHsKG/u9Xrh9XqxuLjI6cnBYMC06Uwmg83NTezu7iISiTBb8mUIMUajEXa7HZOTkwiHw/B4PFyDrFQqnFYSpzgTiQS2t7e5Nluv1zlioOiJappi8XJxG4vBYIBWq2VDSCOmyNDu7u4iGo0imUzydZzFoUyp2VqthnK5jGKxCKfTyVGCVqs9tfabZwG1tpD+ZDAYxMzMDKampuBwOGA0Gr82gYXuUTwmaZTrnAB4r1utVrhcLp6zKZfLmRhC90AREEUlYrLJk9ivlNYnIydmaFKmh0Q8RgGUnrRarfD7/fB6vXA6nbx2iUB3HFESsdyHwyFKpRIbQYfDAZ1Ox0RGvV7Pjgg5V6RBm06n0Ww2UalUDkWIJAZw9JmQgLggCLDb7bDb7ZyONRqNHGkeJ07cCFIqzmAwYGpqCouLi7h+/TouX76MUCjE/WfUUL69vY0//OEPuHnzJhKJBBe7ga9SjVRTo7TGYDDA3bt3sba2xgfpSePg4ADtdhv7+/v45S9/iUKhgFKphLfeegt+v58jnn/+z/85Hj58iP/4H/8jLBYLzGYzrl+/Dp/Ph8nJSSiVSmZYJRIJ3Lt3D6urq/j4448Rj8d5obxM/ptYmWazGU6nEzqdjiO2fr+PW7duYX9/Hx999BFKpRI7E2IDR4tbvGAfN4yVnjcRbi5fvox33nmHD2aFQoF2u40HDx5gfX0d/+7f/TueDXlWU0DE90PU9N3dXfh8PmZVEitxVFiiSqUS4XAYoVAIr7zyCubn5zE9Pc3EkaOatQBgs9m4tpnJZNDr9bC3t4dSqcSH2KiA6nd0yM/Pz2NychLAowiFeucajQZHfkReEkd5RN6iVoMnEX+IiU5OOOl00uzSk265elZoNBr4/X5cuHAB165dw9zcHIxGI27fvo3t7W3cvXsXtVrtWJ5lvV7H7u4ukskkM8GVSiUbQZ/Px3JtFEVTECIet9VoNFCpVFj68WlG0OPxwOFwsEhKOBzmOu5J4dSMoNFoZC1GMhI6nY6903K5jFwuh729PSSTSWSzWdTrdU49UXShVCoPtVEQgaNYLKJQKLBRPA2Qx5NMJpFIJBCLxdhrJJX+yclJdDodzM7Owmw2w2KxYHJyEk6nE1qtlr2sXC7HTNCdnR0eGHxcIC+NtEvF06m3t7cRjUaxurrKtUjysp8HFKUbjUY4HA5MTk5icnISU1NT3EdJ3vX+/j729vb4MxuFdJO4vYXSOMDXBc1HAaQ96/F4mFhls9m4dQX4+nR4Gvjsdru5kb5cLjPTd1QgrnlZrVY+GM1mMztne3t73F9K90Wi+/1+n58ZpeWoDelJRpBKG61Wi5WZaEyUeC2cNUgpxmAwwGKxcIaiUqmgWCwea48tRc/tdpvXj1wu56EF7Xabmd5UiyRnmZyOXC7HZRNx8EKKUUedeyI7Pmkc1EnswRM1gvTBhUIhTE5O4mc/+xlHg1RgbTQaKJfL+MMf/oBIJIKbN28ilUqxdwp85RWSqPHExARsNhvkcjnq9Tob0NM2gsAjxl02m8XOzg7kcjnC4TAAYGZmhpmFly5dQjgcZho7UbdzuRzy+Tz+8Ic/YGdnB59++inS6TRyuRyazeaxXWOv18P6+jqSySRisRjn9emAWF9fZ1k3cb/Y84JqVD/60Y8wPT2NP/qjP2LNSop2P/30U0SjUfz1X/810uk0S0GNAqguVCqVEIvFXpiIdBowGAz44IMPMDMzw20QxK4WQxyhUyTrcDig0WjgcrlQKpWYwTwKoJo/kV/eeecdXLx4EVeuXIFGo8HGxgZ2d3fx85//HLlcDul0miMMIgHRvUgkEq4ZPs0IitWCxH+KU/+jUDcV9zRSpE/C7nRuHPd10ucAfCVwUa/XIQgCNjc3+Ww++tkd/ZM4BOL1+bi9NRwO+Zx8XDbjJHCiRpCaWp1OJxfrScUeAAtMF4vFQ60QlAKlD4no/R6Ph+cO2mw2SCQS7rWhmtxpjxqiRUJDcZPJJIxGI8LhMFQqFbNYxUVkqmOKo19SiCd5teO8BypCA0AymeRomjy9QqHAxJsXeV/y8LxeL+x2O2ZnZxEMBll+jVJMxWIRa2tr2NvbQzqdZkr7qBgaepZEIBll+SlxkzWlAylVS4cPHVpyuRxqtZp/lmpm4vTuqES5lElwu92Ym5tDOByGz+fjHrhIJILd3V2WbSsWi3z/4uwQAP479dSddbr9ZUBKTFarFV6vFwaDgR3pTqfD58dJ7iX67OjzpYhb/Ll+k8PwTZ8/ZQCOjtM7SZyoESQ1/osXL2J6ehpTU1MwGo2QSqXceJtIJLC7u4tf/OIXyGQyyOVyh2pM4gbv119/HXNzc/jpT3/KDbHlchmJRIJV7c9ioR8cHCCfz6PdbsPhcKBWq+HKlSssAn5UlR8AN8Lv7Ozg1q1bSKfTSCQSx9rnQ6B2BkpL0CFIn7NYlul5QEadJmL/5Cc/weTkJN58802mTtdqNcTjcXz22WdYX1/HzZs3uaWCItFROZhIoKBarXJBf1QM9FEQO5mYnhQJ0SFELMdkMsnsuqNiDKMItVqNcDiMa9eu4YMPPuDSwdraGhKJBH71q19hf38fa2tr/GxGIZV+0lAqlZiamsLU1BTeeecdnld669YtRKNR/N3f/d2Z9dge53lFJDqbzQaLxXIqNfgTM4ISiQShUAg+nw8zMzMIBALM7BkMBigWiyiVSvj888+xs7ODfD7POWLaoKQSQYMjr1y5Ar/fz7XETqfDDEaS9TrtzU3pAIvFwiw9v99/qJj7OG9GfBg9Tv7ouCFmyVHdRKzq8iIGkAS0Z2dnEQgEcPHiRXg8Hp5FF4/HkUqlEIlEcP/+fezs7CCTyaBarTJLcZQOY3JWrFYrwuEwDAbDyLBBj6LVamFlZYXbUygdCnzFXG6320ilUgiFQnj77bfZuyZjSJqV1Mt61iAh/Bs3bmBhYQGBQADD4RDpdBpra2uIRqOIRqPI5/MjtW6Ogj5fqtdRq8rjzgHalyRUL1aQofQnZb5u3LjBdV/SfN3e3kYsFkOz2Rypuu6LQixsQJ+j+Jw6iTP+xIygIAiYmZnBzMwMFhcX4XA4YDKZ+CDOZrOIxWK4efMmG8GjURw1aV66dAnT09N4/fXXeXoBFbGj0ShWVlbOrH5DhWoigkxPT2N6evpQ8/mTHppYn/BFiCjPA3Hd42VB0S2lfV999VVcuHABi4uLTM2v1WrY2dnB1tYWvvjiC2xsbLBW5aiO3qE2HqfTibm5OZZ+GpVUoRg0bHV7extra2tQq9WHsg2kdZnNZvHaa69hbm4OVquVU4ZkBEnZ6Kwnw1N612q14p133uEWKmqfuXv3LnZ2drCzs3NsfXAnBVLxMZvN0Gg0LJL/uKiGzkMitZARpM+DhgWEw2G8/fbbAB61LlA0vLq6eqiH9zxDLMR/lIhGLHSx835cOBEjKF7QdrsdOp2O87vEtqIDkhb50ZsTBAE+nw+BQAALCwsIh8Pcg0c9bYlEAjs7O9je3mZJsdMELfTJyUlcvHgRS0tLWFpagsfjgVQqRavVYsHhSqXCYT4ZSLPZzL0woybLdBS0MOnQtNlsmJ2dxSuvvIILFy4gHA5Do9Gg1+thbW0N6XQad+7cYW81m82iXC6PVPrzcRCLjI9KO8Tj0O/3kcvluK+R6mIE6pOjxnLxIF3SnCTZv7Nuj6AGcGr1CAaDsNvtPNZLIpHg3XffxdLSEq5du8alFJrCEIlEmE1+nKPGXgSCILD+7szMDJxOJ65cucItNuKDnRxT4hQQI5X2R7fbhUQiwdtvvw2Xy4WJiQk0Gg2ewVmtVvkZnncDSP2gTqcToVCIW2Oo5litVhGLxXDnzp1jVzg6ESMoHrxKzfDUJEkPL5vNIpFIIJ/Po1KpHFq4VLOy2+0IBALw+XxwuVycViAyTC6XQzabRTabPfVaIKVB9Xo9fD4fwuEwD9a1WCzcc5bL5VCpVJDNZiEIAk8loHQJjWIistCogrxbrVbL9zw5OYkLFy5gYmICbreb5dWI6LOyssLPmcTERxni6QHiw0rcIjEqUSGRyoitR3sGONybGwgEuDeQjDqJPFBNcRQMh0KhwMTEBEKhEEwmEzQaDWdZBEHA9PQ0fD4fpqammIqfzWYRj8c5k0KO9Fml2ekZUAsDEfkuXbr0Nd1NMai+S4pRdA+kjzk3NweLxcJkQFJLIS3YUc2sPA9Iws5oNMJms7HzBnw1aDiXy2F/fx+1Wu1Y1+uxGkE6JEwmEywWC6cGadI4ETTS6TQikQi2tra4PiQGDQJ97bXXsLS0hJmZGVgsFshkMrTbbeTzeWxvb+P27duIRqOsGXhaC0Eul0Or1WJmZgaTk5N47733eBYiNYPv7u4il8vhzp07LCk2GAxgtVqZTXmU8jyqEHu3JHX36quvYnp6GteuXWOR5r29PcTjcdy8eRPxeBzLy8u8UUdJb/NJELdI7O/v8zQMu92OcrkMnU535mlDMSiF3uv12DhTJEtksh/84AeYnJxkoQLg0XSWZDKJra0t7O3toVarnamDIo6GCoUC9vb2YLVaD7VtiFO9tB69Xi8WFhawuLiIbDaLDz/8EPF4HDs7O8c++uhpoMwXGaorV64wi91ut2NhYQH9fh/5fJ57c6m3kdRvVCoVrz86x6jO53Q6OXVNwg1He+7OO0j/lr6ojSyVSiGZTOLXv/417t69i0qlcuxZi2M1guIp706nk5XfKbVE+oykx3c0PUYtFRaLhSWBPB4PT20njyCdTvOHQ2OMTtMTIu1Sr9cLv98Pv98Pu90OvV7P45GIFLK9vc1tAOI2BHH/0aj0IT0O4jlhpFNJOqCk+0qeeT6fRyqV4lE9FOGfl01KhzFlGugQJvLIqDkrYlo6gVJuJDVFa5MMYL/fR6lUYqHwSqVy5pEgAN4fNG2dmq7pfihtSxqUlIkxmUxsgFZWVlCv10+975GMIM3fC4fDmJychMvlgtFohE6n44ibJrPQvqI0IDHJxVGsVqtFv9+HSqVijVOxaAgJUMjl8pHp83wRUJnFarXCZDLxNBvgkWoNTZnJZrMnEuwcmxGksSR6vR6vvfYaLly4gPn5ebjdbqhUKqZrr6+v486dO6wNSh4o9cFMT0/j0qVLePXVV7G0tASfzwez2YzBYMAMsd/85jfY39/H7u4ustnsqdYzJBIJp2l/9KMfIRQKcc5fJpOx2PQvfvEL7O3t4cGDBzCbzZibmzs0gJf6nsSTKEYR1LMzPT0Nl8uF999/Hz6fD1evXoVMJkOn00Emk0GhUMCnn36K7e1tjvBPooh9kqCBpiRhR0r1pNZ/WrMqXwSUhdFqtZylmJubw6VLl7gmSGvt/v37WF9fx8bGBuvFnuVzIsdjdXUV8Xgc8XgcWq0WBoOBHY92u82N70qlEjabDaFQiEeCTU1N4fbt26jValAqlaca2VLpx+fz4cKFC3jnnXewuLjIjd8KhQKlUgmRSIRHk5nNZuh0Ok73EhNZzCqnfmJKi9IgaqPRCK/Xy+PLhsMhksnkuTSElLWYnJzE97//fVy/fh1zc3NQq9Xo9XpIp9PY2dnB73//exSLxRNxqI/FCFLNhGY/ud1upphTGqPb7bJCP2mCUlM4eTd6vR7BYBCBQACBQAAWi4UjwEajgVgshkgkgu3tbeRyOZTL5VOldtM92u12uFwuuFwuWK1WqNVqlgrK5/NIJpMse0b1GYvFAp1Od4hwQXWM027wfxbQoUptEKFQCH6//xBpodPpoFQqIRqNIpFIsOTd09Q5Rh3EQBPPz6O041lG7MTmJJahuL9zMBhwVGEwGHjgtNfr5WgBeORV0x6kiR00neWsMRgMeGj0cDjk9B/drziDQkIPZrOZ5/8RKegs6oEUlZKYNM3TI3FvqifT6+hZkuNM2QVae9Q/S9MsisUi+v3+oSyEUqnk8VLiKTB0plB2bNTOlaOgKNBoNLKYilhOk1rpaDrGSeDYjCB5Q263G0tLS3jllVe4/kViqWtra3jw4AHu3r3LqUyqYVB68a233sL8/DwuXboErVYLmUyGWCyGVCqFTz75BJubm/jkk09eSt7rRe+RJlcsLi7y6BqaxVcoFFAoFLC6uoqtrS1sbm6iVqvBbrcjGAzynDfqlaReLvIMR63HhzYsaVO+//77PMpGJpOh1Wohl8tha2sLn376KdbX1/Hw4UMecDrqm+9xoENDPFaKergonXUW90UHKOntKhQKbjNqt9toNps8YDUQCMDj8eC1115DMBjkSSsAkE6n8fDhQ6ysrGBrawu5XG4k+gMpDU1aufF4/LGvoz1oMBjQbDZht9sBfEWfp+d0EoITT4OYDEOHuFihBwA7KGLeBMkXksgBCX2XSiXW8K3X60ilUuj1eixL6PV6oVKpMDU1hcFgAL/fD7VazRmler3OLWejzsamHmu3242pqSl4PB6YzWbk83kUi0VEIhHmfZzUGXnskSANeaTpzmKR63w+z8ai3+9z5EhFbhrzY7fboVQqebDrzs4O9vf3WVj6tBc53Z/FYoHdbseFCxcwOTnJRr7dbiOdTmN3dxdra2uIRCIwm83weDx45ZVXmCFGqutkAEklJplMolQqndr9fBMEQYBGo4HFYkE4HMbc3BwmJibg9XqZ3BSPx/Hw4UPcvHmTlebL5fK5jQCBr6JfiiyO9iqdFTOU0mR0SBgMBrRaLSwvL/PoLRozMzk5iVAohKmpKaaY0wR2IsNQa8WoOiqPWz/0TMxmMxwOB2ZnZ3k+JSkhUZ3ztPWDyYiLa36dTudQ1kej0XDzP0W6xNilOi2RBvf39xGNRhGPxzmFfXBwwPcfCoW43cpoNEKj0UAul/MkjEwmg9XVVR4DNaqGkJwaEkgnh0AQBNaUzmazKJVKJ3r9x1YTJCNIeW5KZZARpMZdEo2m4q7dbofRaMTc3BxmZ2cxNTXFZBpqHl1fX8fOzg7XME5bGYaMoN1uRygU4uZVm83GLR+JRAIPHz7EgwcPkEgkMD09jVAohD/5kz+B0+lEIBDgg5U2CaUQ4/H4SNUEKU/v8XgwPT2NCxcuYHp6mvsZq9Uqy7395V/+JY9cGsWN9rygZ00OHICvGcPTvh6qK83NzWFxcRF2u52VYmjeJjETZ2dnuR5IFHMSL4/FYlhdXUU2mx1pI/g4EGmO5lKSI+pwODgNT3J8pzVTlEBGkFR6aD+Ia8harRbhcPiQMhRFf5T2y+fz2NzcxPLyMu7fv4+trS0UCgU26NR7PTs7i/n5eR6oS6IVvV4P+XweOzs7KJfLAMD902dNfHocKBXq9/vhdDphNBrZCJKmND3TkTeCtFGJ5UR5b/H/08R1mjROyi83btyA2+3G1atXYbfb4XQ6uTicTCaxv7+P5eVlRKNRZDKZM1GLEKugU48KMbWoFkj1s6tXr2J+fh6vvfYa3G43JicnmVRBn0mpVEI+n0c+n2eG7KgcSGq1mqd+XL16FZcvX+ZRSLTJtre38Zd/+ZfY2dlhGve3wQACOJTRIE/darWiUqkcqq+dBsggU6ptfn4e169f54HNNMbLYrHA6XTC6XTi1VdfRTAYhFKp5NRuIpHA559/jnv37mFnZ4cnpY/KmiNDIb4e8WBcmUzGzvK1a9fg9/tx+fJlSCQSLo+sra1hY2OD04Cneej3ej2USiXs7e2xs9xsNrGwsACdTgeZTMbMdiLDUaqSmuS3traQSqXw8OFDZs8fdVQGgwEqlQrW19eRzWbx8OFDTE9Pw+l04pVXXoHFYsGVK1f4DL19+zYb2MdNcT8rkD1wOp0IBoO4cuUKBz9UOkulUojH4zxpZuSNIPDV4UF6eWI8zgiSISSNwCtXrjCzjbylUqnEs/pSqdSxDYt8EYi9NvHCHA4fTaKm+wuHw5BIJHxY2Ww2jojptZVKhQ0g9Q+OwoFEJB6Px4NwOIzFxUWEw2G43W6e2FEoFHj4L42uGoWNdRwQp0MplSUWNaDertO+JiJdOBwO+P1+WCwWNJtNzMzMMInA6XTC4XCw2gYJpNOQ4M3NTcTjceTz+ZHSmRQTR8TEI6pJazQalrKzWq2clnc6ndw8vbq6ivv37/McwNO+N3KEC4UCpFIpdnZ2IJPJOFNELOpiscgRH5FeaITZgwcPkEwmsby8/MT3oWkw7Xabe1kbjQa8Xi/m5uZgNpvhdruhVCq5Zr+/v8/MWmKPnvV+pUwLOW/BYBBOpxMajQadTgfNZhPFYpHJj/V6/USv51h2NBmAUCiEN954A263myMfsdX/4IMP8Morr+CnP/0ptFotK8YTo0oikbBSAj3kWCyGUqnEjctnAdqoOp2Om46JbEAbVKvVIhQKMdvV5XJ9TSqJ6N83b95EJBLBZ599xjWMszaCVPMMBAL43ve+h6mpKVy5coVZoA8fPkQ6ncavfvUrxGIxJBKJQwzKbwsepxgjJsacdlqJnK9Op4N6vY5qtcp19Bs3bqBarWJubo4bqElUgl6/traGlZUV3L9/H4lEYqSECyjaM5vNkEqlqFarnGGhobGTk5PweDy4evUqbDYb3G43ms0mPv74Y9y/fx8ff/wxcrkcD7M+i/VIzm2xWORBvzqdDn/5l3/JMw6pJNRqtQ6RrmgY7fMqKtHP7+zsIJVKod1uY2JiAjqdDgaDAdevX4fdbserr76KX/ziF9jc3MTGxgav47MEESHfeustzMzMYH5+HgaDASqVCvF4HLFYDJ999hl2dnYQjUZP/Ow/NreWjN3jNPKoAEp5X7vdDpVKxYNySVKNFkqhUEAsFuM8Py2Qs/ZgxF4rgUSXKb9Nm5i+R1Ftp9NBOp1GNBrF7u4uIpHIYydnnBWkUilsNhtcLhfn6KnJt16vsxTa1tYWT9welcP0uHCU4EVRX7PZ5AjjtAkXYn1JYhNTz5jYISPDTQNOiWUYiUSwv7/P2pqjlLqWyWRQKBTcylEoFAA8ov+TfFYwGITL5YLT6eRB0JVKBdvb29je3sbu7u6p1wCfBDJo/X4fhUIBxWKRn424/UE8QUX85/MYcFoTNFQ3Ho9DqVSiWq1Cq9XCaDTC4/FALpfD5XIhl8tBoVBwGvYsQc+dshdEiAEetfHkcjlkMhlks1k0m80Tv95jMYJET85kMlhbW2OlF7GWIRW1aVOLFcPF9TbyAn7zm9+w9BgxnM4y6qBrFIv0UjMshff0OgDMFqtUKszWevjwITcpFwoFHh58locSpf/0ej0++OADlkJTKpXo9XrY3NzE7u4u/vZv/xaxWAw7Oztot9tnvpFOAuTQeDweXLhwARaLBQCwu7vLz+wshM5pLZE2K0UBlC4U1yn7/T6q1SpWVlawvb2Nv/iLv+DUEg2WHZXonQzdP/tn/wxTU1N8kE9MTLBAAQ3LFk8kyWQyuH//PuufjopRp7ON2p46nc7XJiEct0oUnUNEWMvn85xV0+v1kEqlcLvdyOVy0Ov17JCflbYq1bhNJhMCgQC8Xi8UCgUODg5QrVaxt7eH5eVlbG5uIhaLnco5c2xGUMySLBQKqNVqh8Si6bAFDss9kQBsLBZjdtTa2hri8TinF0bBANK1kmwb1S9pJpt4Lli322Vx43Q6zc5BJBJBIpHgfp6zmH/4OJB2odPp5PaUfr+PcrmMeDyOaDSKVCrFB+m30QASxDVB8uCr1SoqlcqZRBxi+n2hUEAmk0E4HOZZm+SAUdM8TRbY3d1lRaVarcZ1oVFYbwTaVxQdAY8O9VKpxAdmoVDgyI90RakXddTuh/A0A3cSggviHsNkMgmNRsN1NLlczhPpKbNTqVSO9f2fFdQRQEMRqDleJpOh0WigUCjwQATSsz2N53tsRpB6x4bDIWZnZ+FwOFhPj4gyYpFfou2Sl/rzn/8ce3t7+Pzzz1Eul1EqlZjlddaeKxk4mtx869Yt5HI5DIdDWCwWuFwuVmkgNRzarGtraygWi4jFYpwiGZUDiZwTmjgwMTGBQCAAuVyOXC6HtbU1fP7551hZWcHm5ubXpn182yCuB1J9utvtshQeKeGcNkg9ZGNjA4LwaE4npWyprkbrj+q1v/nNb7C3t4dEIjGSikQA+ODe3NxEo9HgEUmkJkWRDf1JI6CoRjrqOM3PnNSqbt++jWazCb/fD7PZDKPRCJ/Ph263i+XlZR7Bddp91sSeN5lMeP/991nSj6TxkskkHjx4gNXVVWxubjKD+dwYQTISjUYD+XyeGU7D4RAOhwNWq5XnQrVaLW6ErNfrnPJ88OAB9xESc2oUDCCB0hwSiQQbGxuoVquQSCTMyCKpI7ERrFQq2NraQqPR4OiPhIHP2gASyAgSC08QBBSLRSSTSZ5anclkvpUkmG+CmNj1uOb50wDtLTq8dDod0uk0TzIhY03yUhsbG4jFYtjb2zv2uWvHDUrxbmxsIJfLcT2NooBms4lqtXqoDDFK6dxRAUWCjUYD0WiUFWkMBgP0ej02NzeRyWRYeuy01wO1z9lsNng8HszOzmJubg4ajQYAuCVibW0Ne3t7fN6c1nUemxHs9/toNBro9Xq4e/cu8vk8nE4nDg4OoNVqAXylCJ7JZLhY/+DBA+TzeUQiEW6QHNWpCiRvtrKygmQyiVarBZPJxEaw3+8jHo9zGpFy3KO+aUmRnoxgLpdDPB5nkfN0Ov2taYZ/FojZoUQ2oZ7BsxDQJiOYyWR4vIxSqYTD4YAgCCyhFo/HsbKygmg0ikgkMvKROzm6q6urLB1G5DgyeORcjrIxHwX0ej3U63U+RzudDpdsKH1cKpXOpIYqlUqhVqvhdDoRDoexsLDARpDaRGj0WiQSQTqdPl0B9OP6ReSNHBwcYH9/H5VKBb/61a/gcrng8XgAgD27YrHIk8aJAktTB0bdYJDXTU2vpNlIHjtFscRqGvX7AXAo7VetVg/NmisWiyPVWH2SENd1a7UaqtUqVCoVyuUyz708CxYiXRfVcj799FMWLSdZtGQyiVQqhZWVFX6Oo54ypExPPp/nUUFkCMWMyVFgT486iJdBqeRyuczi3LRuT1tCjYhmVqsVwWAQN27cwMWLF3myEA3K/e1vf4uVlRXs7Oxw7/FpnjfH2vlLC7ZcLqPZbGJtbY31MYlYQgw3Ir1Q6DvKHutRkMTZWRWYjxtUTyoUCpDL5YjFYqzUcBbNx2cFcSsCse1UKhXq9To3mJ+lM0Aq+iSLRfXJXq/HlPL9/X2USqWR6gd8EsjojZJk4HmFmLxHMnlnDTKCJpMJXq8X4XAY09PTMBqNkEql3A6xvr7OLWONRuPU163wNK9AEIQXchkonUQi2uIxJ8Rio6+zPljG+IodeunSJWZqVSoV7gcc9YjiuCCTyaBWqxEIBDAxMYHJyUno9Xr8/Oc/Z3bsWUYlYoo51VmAr7IwRH+nfTXGGGcFUlqi+t/bb7+NixcvYmpqiocj/OY3v8H29jb++q//GrlcjmcinoQRHA6HTyzmn4gGFHklZ9FTNcbzg9K2iUQCUqn00CyzUY8mjhNUe6vValx/U6vVXEs567QcOZHVavXMrmGMMZ4HVGppNBrIZrPcKdBqtbC+vo69vb0z7wU/kUhwjPMJsYYjcLoU71ECRVzU10p1lHFdaowxnh3Uc0tC6PR3ADxOjnpgT9rBfFokODaCY4wxxhhjfKvxNCN4+nzvMcYYY4wxxhgRnO5cmDHGGONYIJFIeH6n3W6H1WqFxWKBxWKBWq2GRqNhpnY2m8XW1haKxSIqlcrIThofY4yzwNgIjjHGOYREIoFWq4XT6cTS0hJmZ2cxNTWFqakpWCwWOBwO9Ho9RCIRLC8v4+c//zm2t7d5+sd3ifA0xhhPw9gIngKUSiUMBgN0Oh20Wi0qlQra7TaKxeL4MBrjhaBUKjE1NYXJyUm8+eabmJiYQDAYhNlshkqlglKphFwuh8/nQ6PRwMLCArNev2us3zHGeBpG3giKp08Qc1E8kuQ8QKFQwGw2w2azwWKxIJVKoVKpjLys1RijCUEQoFAoePbj1NTUobE0NJ6MxukYjUZYLBZotdqvzfocY4zvOkbaCKrVaqhUKkxNTbFYcKPRQDKZ5PE25wFOpxM/+MEPcPHiRczPz+PDDz/E1tYWcrkcj5AZY4xvAolQ6PV6eDwevP3225icnMTi4iKP9SIDJ5bRymQy2N3dRT6f/04KoY8xxtMw0kZQJpNBpVLB6/Xy3CnSxqOBtaMOGiESDAYRCoUwMTGB5eVlpNNpjnDHGC2IxbOfhtPORtBEC4vFAqfTCZfLBbvdDp1OxxEgXVe/30e73UY+n0c2m0Umkzk0kHeMMcZ4hJE2gmq1GhaLBe+//z5CoRAMBgPi8Tj+5m/+Bg8fPkQ6nT7rS3wqJBIJ5HI5PB4P3n//fXg8HjidTqhUKm5MFzenj3G2oDmC9PWk8UmUkhfL/p20YSEDqNFo8L3vfQ/T09NYWFiAxWLh6R/i6yNd3r/927/F/fv38dvf/hatVus7NQ1kjDGeBSNtBAlKpRJarRZWqxXNZhNGoxEqleqsL+upIPFYv98Pr9cLvV7Pxo/m92m1WjSbTRZGHuPsIJPJIJfLodFooNfrYTAYOMqiCe7AV2nGSqXC7Qe1Wg31ev3E67tyuRxqtRo+nw9+vx8mkwkajeaQM0Ui4DRBnOazUfZkbABHG+SIiZ0asYP1OIdslPkR5EzSODKZTMYKMTKZjDkfT7ov0hJtt9sn5myOtBEkb1sikTARoN/vw+FwQKfTnfXlPRUymQxmsxnf+973eIKyQqEAABiNRjgcDtjtdgwGAySTyZFdxN8FENHEYDDA5/NhcnISs7OzePXVVxEKhWA2myGXy3lsUa1Ww8bGBlZWVvC73/0Ou7u72N3dPTEjKBakN5vNuHTpEmZmZuB0Or+WUicZqlKphFQqhbt37yKVSp2YMPEYxwfKQJDBIEPQ7/f5fDg605Ke6yg+W9pXWq0WJpMJRqMRWq0W5XIZ/X4fWq2WxfuPGv5+v4/BYMDDyLPZLLrdLk9OOU6MtBGkCJA8iFH3eo6CBrKK2a3AI/HYarWKWq02Fhk/Y9AmnJqagtfrxdWrV+F2u+H3+xEMBmGxWA7pHUqlUhgMBgSDQVbDt1qt6Pf7KBQKPBT6OEE6pouLi5ienobL5YJer4dUKj0UoQ4GA6TTaZRKJdy8eZMHlFar1RfyoGlihSAIX5v6Mip7kCIJyrBIpVKOMICvRNFppt6oRsOUhbDb7Zifn8fS0hJqtRqazSa2t7fR6XQgl8uh1+vhdrs5Jb+8vMxjtHq93lnfBkMmk/E0eYfDgYmJCXi9XthsNsTjcbTbbdjtdqhUKuj1+q9FgvSskskkisUiVlZWUCwWkclkjj0iPBdGUKFQHDqIzoshFAvIih9ys9nkoa2NRuNc3Mu3FXSwzM3NYXZ2Fj/60Y9gMplgNpt5FBjNVBwOh5DJZNBqtfD7/XC5XBgMBrDZbEgkEpBIJCiXy8fulVN0sLS0hKtXr8LpdEKv1x/yngeDATqdDlKpFOLxOD766COeC/kiAuBkeOl9aNJ7q9ViL30UQLVShUIBo9EIhUIBtVrNacVer4dOp4NarTayQgF0DwaDAaFQCD/84Q/xJ3/yJ0in0ygUCvjwww9RqVSg0Wjgcrlw+fJlNu6EYrE4MkaQnH+NRgOn04mJiQlcv34dMzMzCAQCWF9fR71eRyAQgEajgdlshiAIODg44KwHOS5bW1tIJBJoNBqQSCR8n98ZIzgxMYGLFy/C5/PBZDKhWq2iVCqhVCqNfB1NJpNBr9fj+vXrCIfD0Ol06PV6yOfzKBaLKJVKZzap/LhxlEgiVo4XT2MAwJEE3Xur1ToTJ0Aul0OpVOLSpUvweDx49913YbPZAACRSAS3b9/mocKUglGpVNDpdExwcrvdcLlc0Ol0iEajMBqNiEQix3bIUhnA4XDA6XRifn4es7Oz0Ov1nFontNtt1Go1xGIx7OzsYGdnhwdWPylyoywFzVE0GAxwu92w2+1QKBSQy+WwWq1sTKjdIplMIp/P8xo+DZCxJ8MvXmNutxtWqxWvvPIKXC4XwuEwFAoFZDIZ8vk8UqkU7t+/j2g0itXVVdTr9UMpxdMgNj0JxA2Ynp7G5OQkvve972F+fh4mkwlyuRw2mw0qlQrdbpcdMKfTiUajwYakWq1iZ2fnzM9EcjxkMhmCwSDcbjfee+89TE5O4tq1a9DpdFCr1dDr9ej1elAoFDg4OECz2USj0UCpVOL5s9TXeuXKFUxNTcHpdOKLL77gAdKlUunYntnIGkGJRAKbzcYEAJVKxd5cs9kcGa/ncSBvRqlUwufz8aFCB1Wj0WCP+tsQBdJBqlKpDhXBNRoN5HI5H9jD4RCdTge9Xo+Ny9MO6ZOEmGQSDAYRCASgUqnQbreRTqextbWFvb09Puip1cVkMqFcLqPX6/EBplKp4PP50Gw2oVAoji1SogjQbDZz5Gmz2b6WGQEe1YaazSZKpRLy+TwKhcJTxRgofUgGUK/Xw263c+O9Wq2GQqGAxWLhWmihUIDBYGDCQr1eP7X0Ih2wZLiVSiUUCgVUKhU8Hg88Hg8uX74Mv9+PxcVFVsxJJpOIRqNoNBrodDqIRCJot9s8kJgiqrOYZUdnhF6vRyAQwPT0NC5dusQMcqlUyv2f9Bxp3UqlUgyHQxgMBphMpjNvt6Lno1AooFQq4XQ64ff7sbCwgHA4jKmpKd7nMpkM/X4fzWYT7XYb1WoV5XIZ6XSanS+lUgmpVAqn0wmDwQCZTIZarYbl5WUe+n1cGcGRM4KCIECj0UCn02F6ehoXL16E0+mEXC7nXqdarTby085J4Njj8cBms0Eul6NeryMejyObzZ5ryTQy8uT1WSwWJpXo9XpYrVYYjUaEw2GYTCbY7XYAjw7sdDqNSqWCtbU1xONxfPLJJ2i326dO3Xe5XHC73bh06RLcbjf6/T729vZw79497O/vIxKJMPOT1FfUajW0Wi3W1ta45/PSpUtwuVyYnJyETqfDgwcPkEwmsb29/dLXqFAoYDKZcOPGDXz/+9/HwsICbDbbIbYqodFoIJfLIRqNYnd3F/V6/YlRmlarhVqtxoULF2C1WjE5OQmDwQCr1QqPxwOHw8GGVqvVAniUbq3Vasjlcvj000+h1+vZket2uyf+7PR6PUdMFosF09PTrMIUCoXgdDo5ahIzZq1WK6RSKYrFIhQKBZLJJMxmMy5cuMDiG/F4HLu7u8ygPQ2QsxgIBODz+fDDH/4QoVAI4XCYn69CoeA6NJGd+v0+Op0OP1syOmetAkQOYTgchsPhwI9+9CP4/X688sorUKlU6Pf7KJfLqFQquHfvHhKJBD766CNUq1V2ptrtNmeOKPr7/ve/D7fbjdnZWbz55puwWCz4N//m3yCXyx3bmTGSRlAqlTKryGAw8ENut9totVqnulhfBsSOEjMLm80mL+LzGAVS6lOpVEKlUnF9zG63w+/3sxGk+obJZOI0I3muRNRQKpXY2tpitthgMDiVfjuJRAKTyQSHwwGz2QyNRsMH/O7uLlKpFKdcKBUqCAKz0/r9Pqd+vV4vdDodp3gcDsexkZ3oIKRIUK/X816glgg6/Gh6N7VuPC7LQClEo9EIg8GAQCAAp9OJubk56HQ6mM1mWK1WFqag50zEGIoO3W43stksDAYD6vX6idYIKaJzOp0wmUyYmpqCzWbD7OwsX6/H44HZbOa6JR2kFDVqtVrY7XY0m01MTU2hXq9jdnYWw+EQhUIBzWYTsVjsVB1rql3a7Xa4XC54vV7Y7XaO8oCv+lGbzSaazSYymQyfKeLa2WAwOJOzhGqZKpUKDocDVqsV09PTcDqd7JiQAczlckilUsjlctjY2EA8Hsfa2hqq1Sra7TbXaml/AkC1WsXU1BQkEglmZmag0+kQCAS4N/a4hl2PnBEEvmIWkXchl8vR7/e5HkGyaecNnU6HyTDnsWmZ0jcajQYejweBQABzc3N46623sLi4CI1GA5lMxmw9UjERp2ocDgcGgwEuXLiAvb09KBQKrKys4NatW6jX6ydCgRaDrn9+fh4XLlyA3W7HcDjEvXv3sLOzg9/97neH0rSE4XDI36e+wGw2y5HGa6+9Bq1Wi6WlJRwcHOCLL7546edLKUun04mpqSnodDp2qI6CricajSISiTzWSaTU2YULF1jAgYwgRRRiEQe6BuBR2pB6J+v1OhQKBfL5PFQqFTY3N9Fut4/VMSVn2O/3w+1244033mD2rl6vh8ViOZRqPzg4wGeffYZqtYpgMAiDwQCPx8MCA0tLS5iensbly5eZnl8ul7GysoJut4vNzc1TrakRa/L111/HxMQEFhcXodfrDzFbiYj0u9/9Dul0Gg8fPoROp+Noy+FwoFgsIpfLnXpWibJATqcTs7OzuHHjBi5evIhAIMBatQCQyWQQj8fx8OFDLC8vY2trC5lMBvV6HYVC4RDbmPaLIAiIRCLIZDJQqVRIJpMIBALQ6XTw+XwIBAIIBALY29vjKPJlMFJGkDafSqWCxWLhQxV4RKio1+uo1+toNBrnUnNzMBgwIeS81QPpkPR4PLBarVhaWmISgt/vh9VqPVSrAr6qV4lZX9TuAgAmkwk+n49rAUdTfCd1H3q9HjabDU6nE8PhkL3sQqHAWYYnRaRH2clihRlKXR3nfVDz+9FrehylvNVq8R553PVrNBpYLBYEg0EEg0H4fL5D+0x8AB99H7oniqLdbjd8Ph86nQ4SiQSLCBwHxPXXiYkJrpe5XC6OLtRqNbrdLkqlEsrlMmq1GlZWVlCtVlEsFmE2m9FsNmEymWC1WiGTyaDT6SCRSHBwcACpVIqDgwNoNJpDkdVJgwy3w+HgA93r9fJ1AOCMCNV2NzY2kEwmsbu7C6vVCqvVypkHIsicphGktiKq+128eBGzs7MIhUJwOBxQqVQYDAZoNpvY3d3F3t4eVldXEYlEkEwmeYoOremj5+BwOOSIvl6vMxeEPiM6i45rr42UEQQebTKz2YyJiQmYzWYolUocHByg0+mgWCyiUCicC3bo4yBOh45qv9KTQFHEm2++icnJSfzRH/0RtFotdDods77EaZyjKg90yNKBAwBmsxkLCwtIpVK8qE8aRNumml4qlUKxWMT29jbS6fQzR6JE/NFoNEzJP25QozQx5ygd+bj3ogi1WCyiWCw+9veZTCYEg0Gmq8/NzTEBA/hmrVSCw+GAWq1GJpOBVqtFJBIB8Kj152XXNKXYHA4HFhYWcOPGDczOzmJpaQlmsxkmkwnAo72Uy+UQiUTw8OFD7O3t4cGDB6jVapyeo/skXoFer4derwfwVTM2faaPk8c7CVBLwOzsLGZmZnD58mXu+6QDndo61tfXsbu7iw8//BCpVArZbBbBYBB+vx9GoxHtdpuJUKdlBEm0wWq14vXXX8fc3BzeffddJm2pVCoMh0Ps7OwgmUzi5s2b2NnZwRdffIFSqcT6td+0TsihqlarnD0zGo1QKpU8NJqctpeVnhwpIyiVStnDWFhYgN1uh1KpZDFgYlZSXea8odlsMmuv0WicCyFjSmeSYPPS0hICgQBsNht71YlEAs1mk1MTRJagBU/pJ7VazWo/brcbg8EAOp2OPbzTMIJKpRJGoxFqtRpyuZwjh0KhgFqt9kyfBzE2vV4vb/5+v49arYZsNotyuXzsDs6Tah+UXSBy0ePWFJUXSA6OPnOq+wHPbgCBR9G0RqOB0WiE2WyGTqd7ps/uWUBKSz6fDwsLC5iZmWGClVKp5AMxFothf38fm5ub2N7e5v7IdrvNRJKJiYlDDFa6x7NwPulsc7lcCAaDmJubw/T0NGw2G3Q6HTNuu90u8vk8crkc7ty5g42NDezv76NWq/HnLuZJEFHmNM4SqrNSFHvjxg2EQiH4fD5otVrIZDIUCgXU63U8ePAA8XgcKysr7GhSn+bzfP4UKdKf4nT9cUXvI2MEqQagVCrhcDgwOzsLq9UKpVLJzCFKhXY6nXNtBGkjnwcjSCQlh8OBYDCIhYUFeDweWCwWrnEmEgnE43GkUil+Pu12m3P+3W4XZrMZer0es7OzsNvt7PmScRSLVZ/kIUUDjskIUvREXuo3gep0ZASJEEByarlc7ljr1d9U+KeImwhjRyMCSkFrtVqeLajRaDgCfJF0EtUlyajS7zsOyGQymEwmeDwezM/Pc8uGRqNhIks2m8W9e/cQiUSwurqKWCzGToyYLFEqldBoNE6FcPUs96XVauFyuTAzM4PZ2VlMTU3BYrFArVZzyptS8xQ9ra6uIh6P4+DgAB6Ph7VtSTSdDOdpGHaxCkwgEMCVK1fgcrng8Xg440NTS5aXlxGLxbC2toZyuYxSqfTC73t0DxynAQRGyAiSp2SxWOD1ejE3N8c9UYVC4VDvU7fbPfNF/SKo1+tIp9MoFouoVCrn4h4sFgusVisuXLjA0kdqtRqJRIIX+c7ODlKpFPL5POf6u93uIeYgRR/5fB5erxderxdarZb7tE6rV5DqTHa7nd+/0+k81bGiDSeVSmGxWDA3N4erV6/ixo0bmJubg9VqxdraGmKxGDY3N5HNZo/lWomdabVauY/xqPoQkTvu3buH+/fvHzLAZAC9Xi9u3LiBV199FZcvX8bExAQ3Y1Mt82nXIP5/mlBRqVSwubnJkdhxycVpNBpMTU1hamqKn5NOp0O5XEa1WsXnn3+OWCyGTz75hEkXR7NDFKVS2wRFkWIcHByg1WohlUqhVCqdWJ8gSc9ZrVbMzs7i4sWLuHz5MqampuByuTj1WSqVUK1WkU6n8cUXX+Dzzz/HxsYGcrkcWq0W1xKpP5LWwWm2Roj3ATGGa7UaotEotz8sLy8jlUrh9u3byOfzyGQyL8TfoPchBjqxuIHjVw0bCSMoboSlgrjNZuM6E8mMUZP5KGkXPg+Ixt5qtc4NsYemd1BDMvWNZTIZ7O/vY2VlBdFoFJlMBuVyGd1ul1Oi9KyIgEBN2VKpFI1GgyMRSpGchhyeQqHgyRCPI4I8DpQSps+C+rkmJye5DkJ1O4r0jwPig4BqWUfRbrd5XiApxBz9eZPJxNHH7OwsTCbT1xRnnvT+9Kf4ubRaLVaPoVTXcaVD5XI57HY7bDYbq4bI5XJ+z2g0ir29Pezs7KBYLCKfzx86D4gNqtPpYDQaodfrDzWXA1/VrMn4kCzeSRlBnU7H64ZISRQB0nmQSCRQKpWwt7eH9fV1rKyscPvGYDBgAQoihpxFc7yY6CZWe6KxXdT+kEqlsL+/zz2AL7Knac9RKxYJbxxNjx4HRsIIAl+x9sLhMJxOJy/+g4MDRKNRbG9vs5jqeTSA5w20CD0eDxYXFzE3Nwev14tqtYpCoYCbN29ifX0dt2/f5vSuOO1EC5WYk9T3SdRwIpPQAXpaih2UqgmHwzAajbDb7Wi32wiFQsjlckgmk/xa8nypkfyDDz5AOBzGa6+9BqfTCafTiXq9jlKphHg8jng8zofqcUA8FqlarbLCy9HZgY/bD+RUGgwGhMNhvPfee1y7eVx096T3p9fStXS7XUSjUayvr+P+/fvY3d091v46lUqFYDDIcnQ0TSGdTiMSieCTTz5BIpFAJBL5Wn8iHZaLi4uYmprCxYsXEQqFYLFYOO1L90C/7/bt29jb20Oz2TyREotWq8W7776L6elpvPPOO3C5XHC5XOh0OigUCrh37x7PSM3n81xfp+uhPUHtCPTz4udyWuchpZr39vbQaDTwV3/1VyxPt7+/j1QqhVQqxYzOl2HAq1QqFuDw+/3weDyQSCSHdJdpgsa3ok9QXLdwuVwwmUxMox8MBuxh12q1E+8je1lQVKtSqQ7l7cvlMrd2nIc0KKXiDAYDLBYLTy+nCCAajSKRSHBbwZMiW3q2FOGT8dBoNDg4OEC1WmXlkdP4XIhW3ul0MBgMmGXndrshCAJ7rsRSlMlkrBU6OzuLQCDAjesajYZHvVC67jiNOTkSnU4H9XqdezCBbyaykBdttVphs9lgs9mYvHDUiH7TNQDgpu1SqYRkMon9/X3kcjmUy+VjfW7kMFGqVtwzR58DRUfUtwrgUI2SnhHVno9q13Y6Ha5dUQ33pFqW5HI5fD4ffD4f1/QGgwFrr25ubiIWi2F3dxelUumJqXSpVMqiDKRDfNqSg+QI0TrY3d3lNUmN8OVy+Yk9o09as4+7furnpRFMYm4I1b+P65mNhBEUj6f5wQ9+gImJCR6+2Gg0sLW1xQXiUR89RLp3oVAIgUAAcrkc+XweKysrWFlZQTqdHnnJNwBQq9Ww2Wzw+XwIh8NQq9Xo9Xq4e/cutre38eGHHzJ9+WkLkdiYMzMzmJycxI9//GMeNJxMJrGxsYFEIvFYUsdJgDYyRalzc3MIBoNotVqIxWKslSmRSDid9tZbb8HtdmNmZoZno9Hmr1arSKVS2NnZQTQaPdbDlAwgKdlMT08fGs31JAiCwCop7777Lk+eeFxN8Vmvo91uY3d3F7///e/x+eefY21tDdFoFLVa7VSem1ipiA7HoxMj3G43nE4nfvazn8Hn82F+fv5Q2pdSd4VCAR9//DHW19e5Sf6knFO1Wo1r164hHA7D6/UinU5jd3cXH3/8MTY3N3Hr1i2USqWn9vpRStzv9/PeyWazqFarXH44DUNIe6dSqXD9kiBOUx6FWPT8KBGL2oDEPyuRSGC1WplEFAwGIZVKUa/XkcvlkE6nOWI+juj9zI0gsQ/F2oUmk4mV69vtNhqNBkdRo84KJRqxxWLhNMxgMGA1lLMQ6n0RKJVKWCwWmM1mGI1GZnkmk0meVN7v9w9R7MWaovR3GiBMQtUOh4Ojr3K5jL29PR6YeRqHKfVWEdmKehxDoRC0Wu2heyAyj8/nOyQRBjw63FQqFQu6VyoV1hk9bpABEBsvak6nBnkSI6aGfa1WC4vFgsnJSbjd7kNkim+C+B6o9rO3t4ft7W0ebUMZgOOOoCi9d1QYgAQOpqamYDKZoNfrYTKZODUolUphs9lgNpsRCAS+Jt5AtWmq3e7u7iIWi/GePCkj0uv1kEqlMBwO0Wq1+ADf2NjA3t4eyuUyH+bfRFAiFjXVMhOJBGdSTvNMedwzAnBo74v/TWc8SeCJMRgMuCZLe4tY49SbLG4haTabfFZ8a2qC1Pvicrng9/sxOzvLHitR8GkA7XlojSBVfvLY5HI5G0FSIzkPNU3S6fN6vXA6nZzyW1tbQyKRQKfTwXA45LQVLXZKZ9FkCZfLhVAohIsXL2JhYYEnFOzt7SEajeLWrVtMADiNZ1utVplYQaODzGYzrl69ina7jYsXL35N3Uaj0aDb7WJtbY0FwynFSAr4RAw4zsNITBgTNwcD4AOd3puY0wcHBzwCye/347XXXoPL5TokifasIAZlJpPBzZs3sbGxgc8++4zn3J1E9CSO1OmwFQQBbrcbWq32UEp2cnISV65c4eiY+k21Wi2vP/G9dLtdFItFJBIJfPbZZ0ilUtzgf1J7stVq4bPPPoNarYZEIkEul2NCEaXSv8n5oyhKp9NBJpOhUqkgGo2yEPXTpoWcFo6OU6PvkbaoVqvlyfJidDodZDIZDnbo91itVh5XZrFY2BmrVCp89nwrjCBNjDAajTx/Suy9FQoFxGIxJhucB+NBD1GtVnOq5qwV3l8EVMdTq9VQKpUsZeRwONgroy8qjms0Gq5DUWHbbrfD5/NhZmYGXq8X/X4f+Xwen3/+OVZXV7m59rRk5Kh1g3RLnU4nHA4H7HY7y7vRfVHtsNFooNlsYmtrCwaDAdPT02wAxHWl41BMEYOivUqlgmQyyY3VdMhQ1oFo82QMhsMhD6S22+0wGAzPbQDJGBUKBSQSCayuriIajSKbzZ7o82o2m9jY2IBOp8Ps7CzrB5Nhm5+fR6vV4h47u93Oe67ZbKLVanEKlJwGSrnRZ0kzSan+e5Lrrtvtcu1MEAR26qvV6jM3uYuzEwA4A1Cr1UaGY2AwGGA0Grn9hpw24npQbU+n0x36OTKC5XIZ2WyW9+Di4iLcbjc8Hg/UajVrp/72t79lUtS3wggCj9JKRqMRgUAALpfrkCdRLBYRj8fZYxqFh/1NENPaR2HEyYuAog9qZKdG6H6/D6fTyWk16q9TqVQ87UCr1SIQCECv18PpdMJiscDlcsFqtUKn03HEdPfuXWxtbfG8vtN6tpR22d/fx8HBAQKBAFqtFmcfKGJoNBpIJpMolUqIxWLsfTscDu5XoqGt+XyeI/2TMoLpdBozMzOHRIYfZwQp+iHv22q1HkrzPglHr5to8Pl8nmu3RH4gVt5JoNVqYWtrC06nE+VyGRaLBcPhkPeTXq//GvNYEB5NJaceYnI+xb2BxAqlwdyk2nTSjle320UkEmF1JSL4PA8RTJxWBHCoTDQKRpDKHl6vF6+++ip8Ph+PjyPWv91u/5oRFIRHk4EymQyy2ewh4zY1NQWz2Qy3241Op8NTJz788EPk8/lvhxGkvhefz4dQKITr16/D7/dDEL4aWbOxsYHbt29zD815iATPOyjt4vf7cfXqVUxPT8Pn82EwGKDf78NsNqPT6XA9qN/vHxp0ShEhDf8kb7BSqfAMsb29PXz00UcnllJ7FmSzWbRaLTYU29vbXL+lSdfJZJLTja1WC41Gg1lv1GdGh+pJjPciYkw+n0c0GsXVq1cPkQeIvDQ/Pw+JRAK73Y5isYh+v49wOIxgMMiarGIDePTv4v456vEkQ/G73/0Ou7u72N/fZyNzkvuw0+kgFovh008/Rb1ex/T0NDweDyYmJvigpeeUy+Wwv7+PfD6ParWKSCQCQRDwk5/8BE6nE+FwmO+1Xq8jn8/jwYMH2NjY4JTaSePg4OBQDyXVJp9lzVM6cXp6mhmvGo2GR2YVi8UzGSlHRlmhUMDj8WBhYQELCwuYnp7G1NQUjEbjIWF5ctQ6nQ6azSYMBgOTmujsIOY4fS7ECJVKpSxJWKlUuHRynGfGmRlBKpYajUZYrVZ4vV5YrVZORzWbTWSz2UPF37ERPHmIa1AWi4VbASg6NxqN7InTl3jBHyXIkPFMp9PIZrOsMLO/v39qjNDHgWqQRE5oNBqsgkFkl3Q6jWq1inw+z4dNs9lko0IpYpqHdlL1MSLeiOvJ9HmTIHin02Fno9/vM1NSnFkR46iO5sHBAUuwUQ9bPp/Hzs4Of0anQcDo9/uoVqssFdZsNpHL5QAAdrud02z9fh/JZJKJOvl8HrFYDEqlEq+//jqLC1C6k9KH1Mt2WuuO1siLgIygw+GA2+1m40IN9kQoOW2QASR5u6WlJe7NtFgsbPAotTkcDrm9hdaQWq0G8BXzlWq5BBI1p31H646yH5SpOI509plGgmq1GhaLBQ6HAy6XCwaDgXtoIpEI085p9MbYCJ48iMSTSqWwsrLCupA0IkU8KYL+PDpuR5yyI4eGDqz79+8jEolwc/1ZgSKezc1NPmxowxIpg5qxB4MBJBIJ1ziDwSAPpj3KdjtOHDVQj+sJMxgMLDItHrBKPY5icsjjQOQXYk0SyWZzcxOpVAq//vWvUSwWeRDySUMc/dKMRJ1Oh3v37nHUTo3iVEei+looFGJBb0qJUuowkUhgd3cXDx8+xM7OzrkYyk2pxGvXrmFychJOpxPFYhH7+/uIx+PPNfXkOEApeJvNBo/Hg5/97GcIBAJYXFwE8Gi9fvrpp0w+ErM4aZ11Oh0eDk3R3/vvv8/B0FEmNA2BnpmZ4Va67e1txGIxRKNRVqV5GbbomRpBkoOiD0Uc+qZSqUP04bPOez8vxIXs8wQ6/MkQJhIJ6PV67j2jUT4U5Q0GA+6ZI+9NfN90qJFQ9XEs2uO6z+Fw+MyHCLVM6HQ6aLXaQ2zLkyRXiJVaqAZLKSR6DiQtdfTnHvd34HAKVPx8SAovkUhga2sL2WyWiUun6bBQLZSukVLNSqUS2WyWjSCph1A0ZDAYYLPZDs3mI4JTqVRCLpdDpVJ5YSmv0waRm6j1AwBH6UTEOs3nQlkik8kEh8OB6enpQ9qulUoF+/v7SKfTiMVi3NIm3mvdbhdarZanBdH3dTod13ZJTJwcv8FgAI1GA4fDgbm5OQCPHAQSUsnlcuh2u5wmfd7P5MyMoNFohMvlwuTkJEKhEGQyGXsL0WgUH3/8MSKRCKs5nBeIFWOIGHOeyDFkBBOJBE+0vn//PmZnZ1ncXKFQQKVScZqOJkSQIoa4QbnVaiGXy2Fvb4+JMOdxFqRCoeABwgaDgUk0z1rfeRGI06HFYhHZbBbpdJpHjKlUKiZMiCPyZ1GBodf2ej0UCgXs7u7i9u3buHv3LtbX15FOpzlaPwuDQQ4WpRJzudzX9hHtLZrkQbMHqXbW7/dRLpcRi8WwurqK5eVlZDKZY9M5PUkIgsBiFaFQCC6XC8ViEbFYDMvLy6zNeZrBAWmyLiwsYG5uDm+++Sa63S5LEa6vr+PevXvMmD46NJf2Cs0EvHLlCmf/6DU0IJkENIigJ9ZdnZmZQTabxfb2NgqFApaXl5HP57G1tYV6vf7c2r2nbgRp4ZKorMvlgsPh4HpMu93mh02KCOfBayNQztpkMsFkMn0tfXheIG7IJfKKyWRCoVDgxlcabxUOh+F2uw8N1aQ+NqrVUJP9eREOfxyOshGJ7XdSvZ8UEZVKJSgUCqyvr+Pg4ACTk5PMuCPSweMyD+JrEjcwi3FUyYPIPqMys1OcdheD6lIqlYr1Jf1+P1wuF/fk0Wgrim7Pi1oTkQZdLhcCgQB0Oh2kUikSiQQzKev1+qlnx4jJT2pYRNKJx+PY29vD3t4eS6dRvV98jdS7abVaecAzTZOhvvBCoYBMJsMGjfRvga+MsEKhgN1ux3A45NYmEo8vFAqscPSs6/fUjSCF1Ha7HaFQCLOzswgGg5BIJGi321wUf/jwIUcN5ykVSrVOapY/qlhxXowhSUnV63Xs7+8jGo1yDZeoz9R79eabb7LYtlar5UI4zUW7e/cuVlZWsLW1hWazeda3diwg7UYSOz6JNUqbmQ4/hUKBjY0NvPnmm3C5XFhYWIBOp4PBYOCU9ON0QZ9kAIGv5iNSXyvVhEfBAD4JpOtKNdpr165haWkJFy9e5CntRGza3t7G3bt3uRY46lkIQRCgUqmg0+kwPz+PpaUlWK1WDAYD7OzsYGtrC7u7u6jX66d+bUajEW63m4fpajQa1Go13Lt3D/fu3cPa2hqKxSITxcSgdabRaDA3Nwefz4c333wTbrcbVqsVwCMGbyQSwcbGBj7//HMUi0Um4OTzeTgcDnZ0vF4v/H4/+v0+vF4vEokE5HI5IpEIiyI8a8R/6kZQ3DxJ7EO1Ws0bnupGzWbz3KiriCGeIE3sPFKtF3tIow5KxR1thSgUCmzo9Xo99//p9XquF9JkhbW1NaytrfGAzVKpNNKH6/NArGZUrVZP9JkSE45SYK1WCwaDAXfu3GGG3tHZeVRHHwwGUKvVnJU42jRPtU6q8+j1elYBGtV1KpPJoNPp4PP5sLS0hGvXrmFxcZGHcJMhj0Qi2N7exvr6Oiu0jOo9AV8FCH6/H9PT07hy5Qqmp6c5KxONRpFMJlGv1089oyIIAkeCFMEBX5U7KpXKY4XwZTLZIVUwu92Ot956iwd0a7XaQ72wKysrWFtbw+bmJsrlMg8jrtVqLLwRCoXYeNIMWplMhmazCY1Gg3q9zkOunwVnYgRJJUbM5KLCP034PgldwtMAEURoJhqF+dlslhfKKG9EMYjeTc3jwFdeOPUSUjpDzJRsNBooFArY2trC5uYmN1of58T1s0a320WtVuM5lyeZrSCHJJVKIZvNIplM8lxEu92OqakpnlTu9/uh0+l4Ska322UFD2qmP9rGQtPKxfP7RrWOTUxenU4Hr9eLixcv4sKFC5ifn+e0MK1XYhBub28jm82OdC1QLJHn9Xpx9epVLC4uIhgMYn19ncsKVKs9CxCR0ePxwOFw8JldLBZRr9d5zYnbeEhGkjRdQ6EQbty4gYmJCbjdbhwcHCCXyzEjeX19HWtra8wHoc8knU7DZrNxz3ihUOCG+nA4zCnj4XCIZDKJVCr1zPd16kZQrVbDbrfzF5EoGo0G0uk0bt++jWg0eubswRcFHS5SqZRToY1Gg/Plo55qehrIG9Tr9ZiYmMCFCxfw7rvvYn5+noUOqtUqHjx4gGg0it///vfY399HLBY7F7WY58XTlPNPAlRjqdfr3C9G8x0jkQjsdjssFgsLe5PeIrHqaCArKftQ43m9Xsfu7i4+/fRTRKNRtNvtkStB0L6iCRIzMzO4du0afvCDH8DlcjEzmfoHiYgVi8VQKBRGev2RTq1er4fX68W1a9fwwx/+EFqtFqVSCTdv3sTu7i7W1tbO1JDTGKparcYZA7pu+qIeTooAxdMgLl++zO08Op2Ox0l98cUX2NnZwZ07d7C/v49MJsOMZCojFYtFNBoNZLNZbG1tQafTYXp6Gk6nEx988AG/j9vtRigUwtra2jPf16kaQcoLG41G1pIjVmi73WaKbbFYPFf1M+CrTUr1MnHaiRqAz2uKF/iKQKFWq2EwGODxeJipRXWYcrmMer2ORCKB/f39Qwv62wAxMYaM35P6904CRDXvdrvcA9ftdrnPL5fLcUQuNoLUTE/yak6nEwaDgSdOVCoVFjSnlPWorVHx+iPlGL/ff0gVh5jNNCswk8mgWCyemjj7i0Dc5qLX6+FyuXjiSqFQ4Gnz0WiUFZbOCtS6QBqtTzKCg8GAGaBerxc+nw+zs7OYmZnBzMwM1Go1hsMh8vk80uk0Njc3sbOzg83NTZRKpUOsV8qCiBWaCoXCISINtU34fD6OVp+nf/fUjCAt4HA4jHfeeQevv/46ZmdnoVQqeZYbacMdVcc4D9BqtdDpdFhaWuIHTSDW60lqLp4kKAJUq9WYm5tDIBDAj3/8Y0xOTmJ+fh4AeMrC3t4efvnLXyKRSGB7e3ukPfDnASl32Gw2JpCQEHO5XD7V5yoeZUMpT6qnU12WDFm/30ehUEA6nWbyDPU5kkITjbVKJpOs0j9qkSCVURYXFzE9PY0//dM/ZYaimNmaz+fxi1/8AltbW/jd736Her1+4unql4FarYZWq+V5m++99x7m5+eh1Wrxm9/8Bvfv38fy8jKy2eyZPpfhcMjScysrK2i1Wrh+/Tp8Ph++//3vY2JiArFYjJW9XC4XzGYzFhYWuNWDHMhkMolcLod//a//NWKxGNbX17nn81mUl0gUYmdnB+l0GjqdDhMTE8xZeN5xdadmBMnb0el0MJvNMBgM3IRNRoI08c6jRJpYbowEi4niTsoJo7oRnwbyVKnuR953IBDgdDYxJGOxGCKRCBKJBHK53Lmqf34TxKOViDRCzeunpUP5OJBBJEJCv9/ntUdeNF0bEWNqtRqP5BGr+pAy0yhmYYgxSeN1vF4vzGbzIfZ1uVxGLpfjdohRNegEqseaTCaEQiGEQiH4/X4oFAoUi0Ukk0kWbz/uCSUvApqokk6nOZOg0WiYJKPRaNjpJcHsYDDI02WKxSIqlQobr+3tbaTTaRbEfp5oXSxHl0gkIAgCVlZWUK/XkclknqtuempGUCaTwWQywWw2w2q1Qq/XQ6VScT8HiRaflR7ecUHcr9Xtdjklc16jQOp7pMnYP/3pTxEMBnH9+nU+QEmP8Ze//CXW1tY4AjwP0lTPAzGhhCYS0KzLs362T2va73Q6X0ujHSW+PKkfbxQgCALsdjtcLhdeeeUVTE1NsedPODg4wJ07d7C5uYmVlRVkMpmRnjxDBDoii/yDf/APuC9wa2sLn332GT755BNsbGwgl8udqaNFKJfL6Pf7uH37NlqtFr73ve9xWWtxcfFrDhftlXK5jO3tbfz+97/HvXv3cOvWLe51JG3hF723breLhw8fYn19Hb/73e8OaeA+K07NCIrHgYip2uSFivUJz/phvwgoLUUe3MbGBgwGA9LpNPb29s5tVKRWq5mOTk2yNFOwXq+jWCziwYMH2Nrawt7eHtctzuO9Pg1ipuxgMOBRPVRnG/X0/dFrG+VrFYOEGZxOJ7xeL7xeL+x2O7NcKQKsVqvY3NzE5uYmkyhG+R4pY+T3+zmrQtESlYYymQyq1epzp/dOCjTHMJVKQaVS4ZNPPmF+B3B4TZFxazQaPBJveXkZu7u7KBQKLHd3HJKDFGCIf9/znD+nagSpJiFWtqc0zN7eHjKZzEgv3KeBGssjkQjq9TrXjjKZDCKRCGq12rmsjxmNRjidTly8eBHT09NYXFzklpZ0Oo3V1VX8/Oc/x2effcYjh75tESAAZmUSuUkmkx0iBIwio/LbAJpITqzC2dlZbj2i6JfEHD755BNsb28jlUqNvNKUyWSC3W7HxYsXOcvSaDSwtbWFu3fv4uOPP+ap8aPiYJGx2dzcZMKbx+PhUV7i1DQNoo7H4zwcPZ/PH9KDPi7QOnjR33lqRpCEsff393H79m2Uy2Wef1YqlfDw4UPEYrGReNgvAooEqR+JDkoy8uJZdKMOIk+YTCbMz88jHA5zG4RcLud5c5ubm/jwww+Z1UV9Qt9G0Fw4EgCXy+VwOp3weDyoVqsol8vn5vmeJ1itVvh8PjaCFosFGo2GU171eh1ra2t48OABYrHYyJceSJ2HdGgnJiZgt9uRyWSQSqXwhz/8AWtra9wPOEpMXXLyiLOxs7ODYrGIYrF4SDifRLHFPYTE0n2cmsxZ49SM4GAw4EGlMpkM2WwWer2em43pIB2VB/68IG+kUCgAAOLx+Blf0YuBqOh6vZ6pzXNzc5iYmGAFnHa7zQoWn332GZMQziv551lAkWCtVkO9XueRMg6HA8ViEZubm2d9id9KGI1GeDweFlA2Go1QKBQstl8qlbC9vY379+/zOhyVyOkoSBLNZDLB7/djamoKPp8PWq0WuVwOkUgEX3zxBQ8KHsVeaWpn6/V66PV6yOVyyGQyhwYFEFGLuB7UxnOSYvMvg1M1gqRDmcvloFAouLGSDOTYkz57qNVqhEIhTE9P45VXXsHc3ByCwSA3JBPz7u/+7u9w//59xGIxTm+M2oY9TvR6PaZjP3jwgAkBAHis0hjHD5J8s1gsMJvNLK5RqVSwtraGzz77DLdu3cLGxgbK5fJIEEieBIlEArvdzpJoMzMzsFqt6HQ62NjYwMrKCh48eMAjkkb1PsSSikfVpAhidvKo6yafmhEcDofsPXxbmqe/jVAoFHA4HPD5fJiamkIgEIDb7WZNxkKhgGQyic3NTcTjcVbAGdUFflygOgcRF8QHwKhGHt8GkPKIeDQZnSHUaJ1MJlEqlUaakEWREonQk2IWlUwKhQLy+TwKhcK5WEviJvbzPBkGOMN5gmOMFqgPzmq14t1338Xs7CyuXr0Ko9EIjUaDWCyGXC6H3/zmN9jb28Pvf/97VCqVc78BnhUHBwfMQIzFYsxypsGh35bpGKMMegblchlffPEFPvnkE/zmN79BqVTi2YejiqPKMNRmUy6XUSwWmQl6Hgzgtw1jIzgGQ6wwQhPl1Wo15HI5s7w2NzcPTcT4LoGmsJ9Hlu95RbVaZRZyPp+HUqlEtVrFysoKy7yNItniKIi632w2kcvlsLOzw2o2dI/lcvmsL/M7CeFpnocgCGO35DsGigjFbK+jCiSjnuMf49uDo73FAA5Jxp03YQ3aV+LZj0f31RjHj+Fw+MSxKGMjOMYYY4wxxrcaTzOCY0rbGGOMMcYY31mMa4JjjPEdQzAYZHJGr9dDsVhkAfvznuaWSCTQ6/XQ6XTweDwwGo2wWCyH1GUqlQoikci5S6WOcTIYG8ExxvgOQRAEeDweuFwuSKVSNJtNHobcbrePRcvxLCGVSmEwGOBwOHDhwgVutKeJLrdv30Y8Hsf+/v7YCI4BYASNoFhoW0zGGGOMMV4cJPitVqvx9ttvY2lpCSqVCuVyGTdv3kQsFkO73Uar1TqXOqgSiQQulwsmkwnXr1+H1+vF1atXYbfb4Xa7+d6q1SqkUin+8Ic/jFm+YwAYMSNIkl3UIEsz0ogNNsYYYzw/yLFUq9U8E3JychJ6vR6FQgE7Oztot9vQ6XSHmqDFUeEoj1qiOY9WqxUOhwNTU1McAZrNZthsNjQaDdTrdej1emg0mq+Nkhrju4uRMoJyuZxHc1gsFjQaDbTbbWSzWbTb7e9MY/YYYxwXxMOeaXr55OQkPB4PbDYbbDYbcrkcjEYjer0estksisUiOp0OSxqSRFa/30e32x2ZuiE5zX6/H06nE2+88Qb8fj9ee+01GAwGHvHTaDSQz+dRKpWQSqWQy+XGTvUYjJEyggqFgtMXgUAAxWIRtVqNBySO5alOF+I+QfoS9zdRhEH/d7SXkP4c9Wd29D4o83De62M0vkyj0cBmsyEYDGJ+fh42mw0ajQYKhQIajQYulwu9Xg+1Wo0nu5AcHE0DKBQKaDabqFarzz0F/KTuTalUQqVSwe12IxgMsnE3mUxQKBRotVrodDpotVrI5XIolUrI5XIoFotjIzgGY6T6BP1+Pz744ANcvXoVb7zxBnZ3d5FMJvEf/sN/wP7+PnZ2dsb1wVMCTZSnGZAKhYKnS5DBoLS1Uqnk6RK9Xg+VSgWdTge1Wg3dbnekay9Uf9ZqtZyK7/V6PI39PE/GkMlkPBD58uXL+KM/+iO8++67bCQA8By2breLdruNcrmMWq2GfD6PRqOBUqmEYrGIe/fusWZsvV7nqQBnAYlEAoVCAavVCrfbjQ8++ACXL19mmb9Op4NKpcKTabLZLM+yu337Nk8+GJ8l3x08rU9wpCJBiUQClUrFX2q1GhqNhqd3j0oen9Qr5HI5RxH0RcaCBkz2er1DEZT4HijVRKkn+vOsDheFQgGJRAKZTAaVSgWtVguVSgW5XA61Wg2lUgmHw8H3olKpeEK2UqnkqD2ZTKJWqyEWi6FarY7UgFNx3ZmeF4mGk1AzjUwixiQdlvRMnwSaPj8KZC6pVAqlUgmbzYaJiQm8/vrrCIfD0Ov1kMlkPPar0+nw3Doy/p1OBwcHB7zOtVot5ubmoFarUavVkM1mWULuedeqeP2/yJogh8xsNiMQCGB+fh6zs7MIh8NQKpXo9XqIx+PIZDK4e/cucrkc0uk0D0TO5/Oo1+vn1rEZ4/gxckZQqVRCLpfzYieDOEpGkMZA6XQ6yGQyyOVy/jKZTHzNNIiVDiQ6eOk+aBJBoVBgr5tSOKcNQRAOpcgMBgNsNhsTCQwGAzQaDaampvhZ6HQ6mM1mmM1m6HQ65HI5VKtVrK+vI51OQyqV8nTsUZGEouhVrVZDoVBAq9VCq9ViZmYGWq0Wer0e+XwemUwG8Xgc5XIZBwcHnH57GgaDAacLKZV6VsZfLpdDq9UiGAzi2rVr+NM//VN2ashYRyIRlMtlpFIpjnhlMhmnUAVBQL/fh0ajwezsLOx2O1qtFgRBeGGHTZxaf941QZJ+FN1eunQJ7733Hi5fvoxgMIhqtYpKpYLl5WXs7u7ib//2b5FOp5FIJEZi7Y0xmhgpI9hsNhGJROByuVCv1znaoK9RMIKCIMBgMECv1yMUCkGj0cBoNEKtVkOtVsPv9/OsucFggHQ6DblcDr1eD4VCwbqcAFAqlVCv17Gzs4NsNoudnR0u4NOU9l6vd+IbmCLwpaUl2Gw2TE5OwmKxwOPxQKfTsYi2TCaDyWTiiIhSoRQtarVa9Ho9OJ1OZDIZyOVyPHz4kI081XbPEjqdjqMju90Oq9UKvV6P+fl5NvYUPdy9exeJROJQtCiVSr9m2GhdNptNPHjwAJVKBblcDt1u91Se31GQg2K1WjE9Pc2DWylzsbOzg0wmg48++gj5fB7JZJINEkV/5Og0m01IpVKYTCbk83ns7u4in8+/UDqU1hllSp7H4aP0u91uh9frxbvvvouFhQVcunQJFosF/X4fy8vL2N/fx29/+1ukUins7++zAMAYzwbKAnk8HjidTkxPT/P6rtfrXGOlsVAqlQoGg4GDlyeBau1PAmUhstksD0quVqunMh1kpIxgp9NBKpVCsVjk0TR0yFIN46whCAL0ej2sVismJydhMpngcDig0+mg0+nYY7bZbBgMBohGo5y+IWMukUgwHA65WG+1WrG/v4+DgwM+qKrVKhvCk44opFIpVCoVpqenEQgE8Morr8DhcMDv93P08DSCC20Ss9kMAAiFQjwaplarYXl5mWtOZw2NRgO73Y75+XmEw2G43W6YTCbMzc1xJEhGcDAYQKvVQqfTQavVIhwOHzKCw+Hw0DDdSqWCWq2GTCaDVquFZrN5JgQbOqAMBgN8Ph8cDsehdRePx7G9vY3bt28jm80eipQoSqP7GgwGnPrvdrt8EBJL9Hmvi7Io9Pue52epDcLv9+P69euYmprC1NQUr63NzU2sra3hzp07KBaLyOVyz3V9YxzOIMzPz+P73/8+7+9cLodGo4FyuQxBEJjJ73K5oNVqodFonvh7v8kItlot1Go1bG5uYn9/H81mE8PhkAUcTtKRGSkjqFQq4Xa7YbFYuNbU7/fhcDhQKpVGYnq3RCKBzWZDIBDAG2+8AZfLhampKa4zkcdNkVMwGOQNLFbCFwQBJpMJWq0WBoMBtVoNr732GmKxGJLJJO7cuYNkMon19XU0m80TGVtEpJALFy7A7/fjpz/9KTweD4LBINf7+v0+Go0GarUaer3eYwfokheo1+sP3bvRaITNZoPH40G73UatVjv2e3heqNVq2Gw2zM7OYmlpCR6PBxqNhmtlEomEU9o//vGPUavVOD2v1WpZeYQiJ0ohA0C328X8/Dyy2SxWV1extraG1dVV7O/vo1qtnup9kuGlNCel4YfDIVZWVnDnzh2sra2hWq0+do6deMKBOH0pZvw+r2GnwcRkZHu93jP/rM1mg8ViwRtvvIHZ2VncuHEDWq0W3W4Xn376KdbX1/E3f/M32N/fRyqVGmky1qhCKpXC6XTC7Xbj9ddfx+zsLC5evHgoEux2uxwJEm9Dr9cfWyRIe9NutyMej+OXv/wlSqUSlyVOwhiOlBGkmppOp2OPcTAYcKpxVNKhKpUKOp0ODocDHo8HgUDgidem1Wq/9j06WIjwo1aruanXaDTCarWiUqlAKpUiFouh3++zR3Tc9yKRSGA0GmG327nfymAwYDgcotPpMKGAUrSPa1Mh0gzVFcmYUBRP3ztrUG1Wp9PxdG+bzcZREj1DSlvL5XK+XzIovV4PzWaTSU20NilFTJ/lcDhErVZDMplEOp0+1fsUk7XEjhcxQSkFSsNoTytCHw6HTBSjf38TiMhEDlUwGITf7+dMS71ex97eHs8XpCj8LFs4xK02wMkIDBw9b47rPdRqNafSzWYzDAYDrx+VSsUEKuDReU28DXLyv+lan+RskUMpkUig0+nQarWg0+lw+/Zt9Pt91Gq1E8umnP3J9CWo1ra0tIRQKMSit91uFxqNZmRqgseBo/dBBoMWlM/ng9VqRTKZRC6Xw/7+PtrtNjcvHxcozVCpVLh3qtPpYH9/H4lEAuvr69jb20M6nWaR5ccZQY1GA41Ggz//8z/HzMwM5ubmDt2r2MCcFVQqFafSwuEwHA4HjEYjs3nFoEOM0vCpVOoQ5T4ej6PX66HX68Hr9cJkMsHv98NoNCIcDnOdRKPRcHr7tCCTyaBUKmG1WuF0OhEIBGC1WjEcDtmjjsViSCQS7NmfNp7nMNPr9dDr9bh+/TrC4TDee+89WCwWtNtt7O/vY3V1Fb/+9a9x584dpNNp3idnQUiidUOZA9pfYkfqON5DzEantUXv8bKREvWGFotFTpWrVCoolcqv3QNlhigy/Kbrftz9U/2ZDKrRaOS9EwwGsbOzg52dHdRqNTSbTS6THSdGyghS7YxIJNSUKx7wOgqgsJyubzAY8OKkB03fp+hJvFDocKQIhBYzGUOZTAaHw4HhcAibzYZarYZ0On3s1Hta1JTnj0QiTJtPJpPY2NhALBZDJpNBpVJhosfRxUzRXrlc5lw+cHgg6lkZQSJ1UH0sEAjA7XbzGju6rg4ODrieRypFxBLd3t5mI0gecbPZhMlkgkQiQafTgd/v57YCm80Gr9eLXC6HwWCASqVy4kV+SsvrdDqeoKDRaNDr9fjaK5UKE1tGpXXlSSCHwuFwsDaoUqlEvV5HOp3G1tYWR7XEWD2LexJnPjweDwwGAw/9LZfL3ItJX71e75nXAp0RlHGh9COxlYfDIZOVyJl9kc+Asj+NRgPZbJadKSLAnASkUim3whmNRm6J0+l06PV6LN5A2aWTwMgYQalUCo1Gw6kOjUZzIlb/ZTEcDnlB1+t11Ot1NBoN9mTIQFYqFTQaDUSjUWbVkVGYmZmBzWZDKBTiBUbN6ZS+cjgcUKvVWFpa4miEms+P814GgwFSqRSq1Sr+xb/4F5DL5Zx+KBQKqNVqaDQaTIR4nKdJaUZq8QC+kusiBuk39didFNRqNd588034/X5cvnwZbrcbPp8Pbreb0y+EwWCAbreLnZ0drK2tIRaLoVgsctSUSqXQbDYP1Sf0ej20Wi2KxSJCoRAmJyehVCrh9/shl8t5PW9vb+PmzZsnXhukA8Tr9SIUCmFmZgYajQbVahUPHjzArVu3EI1GUa1WzwVr0mq1IhgMYm5uDhMTEzAajdzecfv2bfz7f//vkUwmX+rwf1lQNONyueDz+fCP/tE/wuXLl9Fut1Gv1/HgwQNUq1VuvUmlUixG8CwQy965XC4sLi5yKl8QBHS7XXz44YfY29vDhx9+yNHw82I4HKJQKLCDtLW1he3tbc7EnQQUCgVMJhOcTicmJiYQDofhcrmgVqsxGAwQDAbRaDSgVqtPrM57okZQzDQ72igufg3l/K1WK7MRpVIpR1CkbD8KXutwOOTeqgcPHiCTyaBWqzGDkKLDeDzOEVy5XEYikWCPrlarwWq1ot1uw2w2MxFFnDqjfjaTycTe70mQY8QN3rFYDFKplCNYqheRcsqTUjpUHyPDQDVPcc3gLIygWq2GyWRCIBBAIBBAOByGxWKBxWKBXC7HcDhEq9Xi6200GshkMtjc3MTKygri8ThKpRJ72eVyGZ1Oh6NdSj91Oh3k83no9Xo0m00mSFmtVshkMrjdblQqlVOpi1KGgdaNWq3GcDhEsVjE3t4eVldXWRt0lI0g1cpdLhcCgQCcTifMZjP6/T6q1Sqn7HO53CEW7lldq9VqxdTUFC5duoSpqSm43W4mkXS7XTQaDS47kHrNN+1n8VmgUqng9/thtVoRDodhNpthNBpxcHCAdrsNh8OBarX6UqUHcvBJZq7VaqHRaHC68iRAAhzNZhMGgwEul+vQ/4vPlHNZExSrqFAUJAYZSIVCgWAwyPUVjUYDqVSKTqfD7LV6vT4SRvDg4ADpdBqVSgXVapWNGPWckUzYvXv3UKvVWEWlVquxI7C2tgaj0YhSqYRAIACLxcK0dgKJBdhsNhSLRWg0mmf2HJ8X7Xb7pdibj5s8QD1hGo0GOp3uxDbRk0DsW4fDwe0Qi4uLHHnT9VarVU5n53I53L17F8vLy/jiiy84QiYijJgVSmg2m5DL5Ugmk1CpVKhWq1Cr1dyE73K5EIlEUK/XT+UzUKlU0Ov1cDqdsNvt0Gq1qFQqSCQSePjwIX7/+9+fWS3weaDRaOB0OjE5OYnFxUWEw2FYrVa0Wi3k83k8fPgQ29vbSKVSZ34uqNVqbi366U9/iomJCVitVk6Hms1mZj9SXYvq60+DWFiA2NYajeaQIEe73Uaz2YTH4+ExUS8DStee1FlzFGq1GqFQCNVqFRaLBaFQCMBXpRpqxznJZ3wiRpDqEtRESZ7340JqUqe4ceMGJicnYTQa+XWFQgGxWAyxWIxVLc4aVEOjh1MoFFAul2E0GmE0GjlVur29jVarxbn/brd7qI2CUnFEZJDJZI/14DqdDqc3RtVzNxgMXNAmRZJer3dIfuy0Dl1yJtRqNRYWFjgKdDgch1iqtVoN9Xod6+vraDQakEgkyGaz+Pzzz7G3t8dtDeLP/kmfv1iKjVhyUqn00Ay700o/UsO/1Wrl1GGxWMTW1hY38I/qOgK+4gY4HA4sLCxgbm4OU1NTkMvlaLVa2Nzc5IiW6uRnDaprmc1muN1udmZpf1PERkaRvr7pOYjPAwoWKCqkskm/30ez2UQqlUI6nT6zmuiLQMwDsdvt3K4EgGUkc7kcCoUCZ6NOAidiBCmVR3JaHo+HtSgf91qDwYBXX30VTqeT2yMAoFqtIpvN8niXUXm4pK9IhJJyucyePy30ZDJ5yNMTpwdpoYol1x6XKiNP6Kw1Rb8JOp2Oow5ikdHmpDlup0VZJyNoNBoxOTmJUCgEl8sFi8VySPas0WigUChgY2MD5XIZEokEmUwGy8vLLLD8POQFepZkAKkPjhyBer1+Kk6cWPaO0vPVapUJMWehYPM8IIKJxWJBOBxGIBCA1+tlhZloNIrd3V1Eo1EUCoWzvlwAX12zVquFyWSCXC4/JD4gzvAQxAbucS0jlKI/+lrx/1Mpg6LjQqFwLshOBIpwDQYDt4hR+p5KMsViEaVS6bn24vPiWI0gpTy9Xi8cDgfef/99+Hw+LCwsMAPo6AMlL5oOKWJMAuCaIHmvarWaWZf0oM9a5b/f77OqfqlU4sUpPvS1Wi3sdjt/TU1NwW634/r166w2Q6ky+nkiYNCGp6hkFBEKhXDhwgUEAgGYzWYWKt7Y2MD6+jrW19dRKpVO/Dpo/VH08P3vfx8+n49rrlTvpF65aDSKDz/8EMlkkmuCqVSKU0LPsq4okvf7/QgGg8zGPDg4QDabxdbWFtbW1rC1tXVqDdzivkaaqLC3t4dKpXIq7/8yUKvVmJqawuLiIm7cuAGPxwOlUonNzU2k02n8+te/Zkm0b/o8T6qX7igoYllbW8Nvf/tb6HS6b9SZJe1ao9HIWSByHOmL1rPP52NBB2o1oNesr68jFovh7t27iMfjIyVW/zRQT7HFYsHU1BRmZmYwOzsLtVrNGbZEIoG7d+9ib2+PR3udBI7NCIopwlTMnpubQzAYZCP4PA3vFCmpVCpYLBZ0u11mQhF7aTAYoNlsnumDJ4NHRu9oCoMetsPhgM/ng9frZSNIlO+j9F8ibNRqNRSLRSZknPUMtyfBaDTC7XZzOpSa7Mk7Jfr6SYMcKofDgYmJCQQCAZZ0EqebqQ2iVqshkUhgf38fEokE3W73uZpy6f3Ew6CpcXgwGKBWq3E6p1QqnUokKE670fsRgYcYu6chxfeioJmiTqcTTqcTGo2GJQbj8ThisRhyudwTOQL0TMTSb8BXjoGY0HRc9z8YDNBoNLhlg/bB06DX6/nAJ86EmANBJBeKlCQSCfR6Pd8L1e0ymQx/JqVS6dxEghQhk5avxWKB0WjkZ9NoNJhRS5HgSQU7L20EadGpVCpMTk7i4sWLeO+997geo9VqoVarX6jH4+rVq6xf12q1kE6nkc/nsbKygkqlglKphC+++AKxWOzM2W606SglRvUhrVaLiYkJvPPOO5iZmcHU1BSnfYkARN4dSVP1+32OADc2NhCPx08tnfY8oGfvdru57UOlUiEajSIajWJzcxPxePzU6mHUqvHqq6/iJz/5CXw+39dYt0fTSNVqFeVy+dD/PQvoeRNRYWpqCpOTk3xo5/N5xONxbG1tIR6PI5vNnooTQ9NIUqkUZ18CgQDeeecdTtPRehrFIdUmkwnvvPMO5ufnMTk5iUwmg729PXzxxRfY2dnB9vb2oV5UMahmZjabmV1Kjig5B5RZKpVKxzYcuNVq8diw1dVV7uN7EgRB4FJRIBBgxSFKa+bzeeRyOeZLKBQKJgZRIJDNZrG3t4ebN2/i4cOHiMVi50osXCaTYWZmBpOTk7h06RICgQAUCgWz0SnaL5fLPOrrxK7lpX+BTAa1Wg2n04lgMIjZ2VkEg0GODEgolw4YMg6Pa4AnAgl5smT9aZKBQqGAXq/nOke5XEa9XodSqUQymTzUSnHSm/toxEe1PVq0pABjsVgQDAYRDofh8/ngdDoPRQwE8oCIXUqjfMTsxFFb4OK5g+Lmc9IarVarpzp8lZwPSh3RoShuz6HPWRwtvcj1icUNqB3CarVCoVBwvbhWq/EmPq3PgYx7uVzmGiCpEE1PT6Pb7TJjlFiiZBBHQW9TLpezfKBarT4UFRDBSuwMihmUpDc8NTXFEQbVaLvdLqfBa7UatwI0Go2XPiuoTaZarXId+JuYwMQibrVaUCqVHAkSx6BcLkOhUECn06HZbKLT6Rxy4BqNBqu6ZLPZMw8CngdititN3CFCDCnsVKtVlEqlEyXEEF7KCJLOm8fjwbvvvosrV67g7bffhtVq5Vl7g8EAmUyG6yx6vR5ms5mNmhg0RaJerx8q4tPrqQ0hHA7zpr1y5QpisRj+6q/+CvF4HHt7eyznc1IQK6BQK4Ner4fBYIDT6YRer4fRaOQoMBQK4bXXXuPG6sf18hAFv1KpoFKp4M6dO1heXuY+xFFb4PTs7XY7HA4HrFYrp4CoKTibzZ6aaDY5IjT26ShVXBxp93q956r7Pe39aOTU4uIiR4KtVguZTIZTrfl8/tQEtGmt7OzscNuH0WjEq6++itnZWVSrVWxtbSGfz/O13bt3D4VCAfF4/EzTaWLBDMqW9Ho9lMtllEolnkspfr0460JqQH/2Z38Gv9+PixcvsrIKaeDeu3cPe3t7+Lf/9t8inU4fi3IOsaF7vR63Qn0TnkR6EeuNEtFGzAcgA5FKpbC9vY2trS3s7u6OXET/NBB5y+PxwOfzweVysV4xtWpFIhFsb28fGmp9UngpI0iMR71ez2NpjEYjiynTHLloNIrhcMhz2cSK9gSSldrY2EChUEA2m2UvgHLsNpuNoyzqPyM21o0bN7iZtFarcYNzs9k8tnwyeZxqtZo3HjUmu91uuN1uJoeQJ2uz2XhmHXl8R1NzRAAiAkM8HsfOzg5SqdQLqz+cJMiT8/l8ePXVVzE9PQ2LxcLCBqRNKR6JdZIgirrf78f09DTcbjcTYY4eNqT8sr29jfX19RcmG9FA3oWFBSwsLBwiOABfr0GdFohank6nIZPJcO/ePc7SkJGhflyDwYBSqQS5XI5UKgWNRoNCoXDqLFIxOY4EM0hliKLacrnMaXVqFyCxco/HA4vFgkAgAJvNhunpadhsNp7oQmUJmUwGv98PhUKBV155hecqUpR4XHiW5/0sr6GeT0rpA2BHOZ/Ps1bqk2qj9KfYsI4CTCYTT5chYqBEIkG9XkcymUQymcTOzg6Tn056Hb60ESTiyuLiIgKBAOsokgIJsQRJOYOYkGIPiNKA+Xwen332GeLxOKLRKBsAihrNZjM0Gg1Hg7Ozs/B6vQgGg9DpdCgWi7h//z4ymQxWVlaQzWaRTqePrTmYNiv1PxIVPxAIYGFhAfPz85ibm4PdbofZbP5a28NRCrSY3FMqlRCLxXDr1i3cv3+fqfqnMVTyeUHOz+zsLP78z/8coVAINpsN+/v7SKfTWF9fRyQS4QPmpEGplYWFBXzwwQecDjuaCgWAYrGIzc1NfP7557h79+4LR6oqlQpmsxlvvfUW3nzzTVaHOWuQ8SI2qFwuRzgcRqfTgdfrhdPpRCgUgkQi4XRgKBRCNBqF2WzG6uoqCxafphGUy+Xwer3weDycHqPUOqX8CoUChsMhj7UKBAK4cOEC3njjDczNzcHtdvP8RyIsHZ0MQmouMpkMd+7cwR/+8IevsblHBQaDgY05DRAgJmoikUA0Gv1aU7t4vT+NGHRWEASB5eUmJyfZZnS7XZTLZWxtbWF1dRX379/nwQEjbQSBr4Yw+nw+mM1mSKVSLjhTJEc1MKfTyR4zRUDFYpGnq+/u7uLu3bs81JR+ntJbJCBrMBiQTCYRj8cxOzsLp9PJKh0LCwvweDwwm83IZrOs1Vcul7G3t/dSdQ+HwwGLxYL3338fDoeDG2OpOdlqtTJF/nFEIPLKqB5F0dK9e/d4dmA6nUY2m0U+nx/JWiClHCmV4fV6ufZbKpWQTqeRy+VQLpdPtLcH+KrZ1mAwwOv1wu/3IxQKQa/Xf02qj1oFkskk9vb2kMvlWC3mWd+L+jy1Wi0/f4PBcEiIm+rVOzs7iMfjyOVyp1pro7VCda/V1VUUCgVUq1UuJ1gsFl63NKiWSEVEpnn48OGp9eaK66skHEHkFUqDEq+AosVLly5hZmYGly9fZsUm0rytVqscEZMyEBkSi8UClUoFr9eLZDIJs9nMZJNRY1Zeu3YNV69exfT0NBwOBwcXdLYeTRWScDqtU5ruQucxieOf9VxPp9OJcDgMj8cDu90OmUzGhK5YLIaNjQ1kMhmUy+VD7XAnhZeOBIkYY7PZOKylugs9IKqFUSRHPTG9Xg+FQgGFQgEPHjxAJBLBzs4OyuUyCoUCGwCxdBCRT8rlMovm1ut19v59Ph8bIofDwUoh2Wz2pYdtUivA66+/jnA4jJmZGSb5iJukv4kJSwSgVCqFeDyOjz/+GHt7e7h//z4bSLFm3qiAnoFGo4HL5eJaILHwSHSbSBcn3eBPRpCMksvlgsvlOuSEiMkERCQgp+h52HRkBEkZhFpcxO0XdEBRWieXy3Fq8TRBLSCU5qtWq2g0Gpym9/l8MBqNPP6JhNwNBgOTMCKRCB9CpwH6fOVyOSQSCbeYkEg9fYZGoxEejwdXr17F3Nwcrly5wmQ0EjgnzVtigHa7XSbb0JgeMqYGgwHtdptHH43CfqOM08zMDF555RV4vV7odLrHptrpTKQaNekMazQaft6kbiX+TM/qPiUSCSwWC1wuFz8TUr6p1WrIZrOs2XtaAxReOhIkYgh5xMBXD5GYkJSK0Ol0rKaSSqVQLBaxsrKCTCaDW7duoVgsIplM8uYV57IpcqRFTeSDfD7P4rVmsxkTExOsWelwOGAymQA8Sl/du3fvpe41nU6j1+txipJGIhGOpt7o3+LNRWSFQqGATz/9FNFoFLdu3eLxNqOQsngcaJPR8N0f//jHuHjxIjQaDZN5Hj58eGi0zYl7cF+SIWZmZvAP/+E/ZAV6sShDv99HKpVCMpnEp59+irW1NTx48ADxePy5GJtkcCkdL84EEAaDAaeqtra2ONI/C51OcqDq9TrPh6P6mM1mg16vx+LiIqcfzWYzZmZm0O12oVKpsLm5yWn60zSEFBVSpENz5IgYd/nyZUxNTeHdd99lp3p3dxepVAr3799HsVjkyJGcnMFgALfbDZvNhmazCbfbzdmi6elpSCQSVCoVLlGcFcjJXFxcxIULF3D9+nVuM6NzRqfTYWZmBlqtFktLSygWizymTSqVciqY1qpareYZgR999BGi0Sh+9atfnbpjRteu1+sRCoW45YM0kYvFImKxGPb39xGPx081e/LSRvBJRVmaf0WhOTHzxPWvTCaDra0tZLNZ7O/vM4PrSRGQuNGV1BUoAgEAi8XCBtnpdB5qXXjc7LjnBW1Kus7BYPDUicriz0N8PzQpvlqtshA3/b5RBUW75GGGQiHY7XZIpVI0Gg3k83lks1muYxKl+6SviajwRIYg0hIZwcFgwGna3d1drluSI/M810jriUhZNJSX3kec2SgWizz66qwOVrGQg5gA1O/30Wg04HQ6odVq0ev1IJVKodfrYbFYYLfbuZmbeihPA2InkrJJ9EWOtNPphNvthtPphFwuR6/XQyaTwe7uLtbX1w8Re8TtUuQ4l0olbj4nUh/16b3o9IVvuicq54jZ8LTu6H3FfcYkMEKkEbGYBgkzCILAkXuv1+OfJ8Utkq6k3rtGo4GVlRUUi8UTuc9nAWVRzGYzl8jo/BBnkSiVf1p4aSPY7XZRrVaxu7vLY2qIvaXT6bixk8YK0bTi9fV1JJNJRKNRlh0jr+1ZQIs7n8+jWCwiHo9DqVTi4cOHMJlMCIVC3DeUTqePRbWE8um3bt1CqVRidprf7/+aQgVd4+Oum1IA09PTkEqlWFtbY+MxqiB5MGIaXrt2DQaDAQCwtbWFL774Avfu3eMBtKcR/UgkEnZ45ufnDzGPCe12G/f+/+x955Nc93Xl6Zxzzt2TZzCIBBggiiIl25K9u9b6w8aq/ef2y1ZtubbW9pZM27JsSQRJEHkwOXRP55xz3g/wvXwzHIAIE3rIPlUokiDC637v/W4659ynT7Gzs4OvvvqKyVKvMsR+1d9H6608Hg+zYuVyOc9Bf/vb32Jvbw8HBwfn5pTzplCpVLyxnbx6iXVNZAy73c6ElPMmjQg1s6TlNJlMUCqVWF1dZSJcOp3G3t4e/vVf/xXr6+sIh8Oo1+vcUSEmKQUg2vdJSSsFi7Nc2K1QKLC4uAi3243r168f0agCgM1m41mo0CaN3I50Ot2RJFsqlXLgtlqt3ykY6NcKnXO2traQyWRweHiIZDJ5YUlZIBDA1atXWUuuVCrR6/UQjUaxtbWFBw8eIBwOswfqeeGdgiBlWNVqFeFwGJ1OhysjqtBarRai0SjK5TIikQiTXqLRKAqFAqrVKjOA3qZyEG557/f7yOfz6HQ6zFylbFY4V3gXDIdD5HI5qNVqxONx9Pt9nkGR4HUwGBwZ9hNTjb4bklZQG8pgMPAeuvMYBL8Njushqe1CPqHUAj2PWaAQwkPuuPkAVe6kWSyXy6/lPkH3jua8SqWS11qR/ysRTCjzpr2DwkrzrAIgtcZe1/6Mnk36TE6nEw6HAz6fjxnbZHx+vHV/XlXDeHzULH48Hh/ZRzkajdidR61Wo9vtolgsIhwOIx6P8wYF4SwY+JbIRe8ayS9oLk+2i6c9fycplV6vRyAQgM/nw+Li4kuDILE/xWIxk+yOV6g0DhISfugZoMAv3ExDCQS1GEmvet7nC30uk8kEj8fDbWx6Rykm0A7W8w7S7xQESdt3cHCAv/7rv8bVq1fx4Ycf8sFPG5/v3buHVCqFtbU1dtU/i9kXzWTIHBn4thV5Wn8XMe5yuRwvuqQ9XiKRCMlkkgWzVDnRskitVssHDunsxuMx79Ai3c8k7nojzZLP54PH44FOp0Oz2UQ+n8fOzg6ePn3K1lHnbcd10mE9Ho+ZQby2toZoNMra0+8DtZKIqu/z+aDX6+Hz+bgVHAqFMDMzA7lcjvF4jEgkgkgkgvv373N34rQrKDpMDAYDgBcMUOGBehKEJgK0g+5nP/sZFhcXsbq6CoPBAIfDwYxMkk10Op1zaWkD37ZtiQ1KM0CDwcDtWWJ4ut1u7u6sra3h888/55FKKBSCQqFALpfjjpLFYoHT6cT169fZuIL2EtKi4UKhcKq6SJrt0bvyq1/9iuUcQmkU8ILoQ8GeQMmX8Lnu9/ucZOZyOd4BSsYP0WgUvV6PK0Wn08nf5/r6OkuXLiLI0Bq9ubk5fPDBB6ylpkRmfX0dT548wTfffHMhZ987t0PJ6md7e5s3HxBbKZ/Po16vY3d3l2dflMWcJd4l4FGAolYf6fiE9krNZhMSiQThcJh/ntpwZHVGrTOn0wmDwcBsKCJVEHmHDlWRSIRqtYp0Oo18Pj9RsggAbA/mdDphsVgwHo85AcpkMmzyPSmVLF0fzeZardaJFaqwYgdeJDl0+BKxa3FxEUajET6fjy3SjEYjRCIRWq0W2u02YrEYYrEYqtUqz3dP+3ugZ2pxcREikQjhcJgNIU565ikRoyTMbrfDZrPh2rVrvGKK5vbU0SGjBhohnMecmmRDJIpvNBrcdnY6nSxloTauTCbjZGs4HEKr1QIAE0b0ej1XhQ6HA36/n1uSNCMWBkCaQZ3W/aLgRR0Ko9HINn5Cwha1fOm7J1cjak3TvRGJRPz9FAoF7O/v88Ju+v0k/6I5JwVB+pzlcpnP3/N8P4WuYnR2UIVLdnjlcvlC5+fv3A6lFkaxWMTW1ha+/PJLDgjk9TeJc5GTIPQfpOqMpAxCe6VGo4Fut4uNjQ0kk0lkMhluw1BJTw8zaclos4bH48HKygpLSkQiEVZWVqDT6fjgJGr3pARC+l4MBgP7wo5GIxQKBTx//hyxWAzFYvFcLI6OX9fxH0JGcbFYRDabRbVafSkRRkgtJ2mB3W5HKBTC7OwsHA4Hbt26BavVCp/Pd0TjSgLfcrmMnZ0dHB4eolwuo91un8n3QFrZ27dvQyqVotVq8Xok4YxTSLrQ6XRwu91YXV3FysoK5ufncfXqVVitVvZrJLuvZDKJ3d1drK2t4fDwEJlM5tyCIPl60mzVYDBAp9MhEAhAJpNhMBhAJpPBZDJhMBggn89zx8FisfBqMqPRiL29PQwGA0gkEmYPu1wuGI1GlMtlFItFbG9vY2trC8lk8rW2vL8NqKNA7jxEkKFdk4PBgMdBQk2mXq9n7TG1N+kzk5k4GW33ej30+30cHh6eWAkSW/YivEWFbdDl5WUEAgEmY0kkEg7qpNm9KMOCU7O4oPlgrVbjA+k8zE9PEyKRCEajEXa7HT/96U8xHo9Rq9Xw+PFjZLPZI9k2ZZS0WJd+P80e6QGo1+uQy+XY29tDIBCA3+9nj82ZmRloNBpcvXoVNpuN5QaRSIRZshcNmiMZDAYOBHa7HaPRCNlsFo8ePUIymTxRbiCcQ9F3d5oZt5AtPBwOj7SPRCIRU+I9Hg8AMGtQuHpLq9VCo9HgypUrGA6HKJVKWFlZwc2bNxEKhWC1WtmGjVbf1Go1NmE4PDxELpfD48ePkcvlztTxnmbfuVwOFosFv/zlL/lQFb5zxAiljQpmsxlerxc2mw1ms5m3LNCvz+fziEQiePjwIR48eIDnz5/zWp7zBCUhqVSKW5+kRaVui9Fo5ATx9u3b0Gg0/P9WVlagVqsRDAZ5pkgLW1utFrLZLO7fv49UKoXHjx8jn8+fCSubKttsNgsAePz4MRwOB1vZSaVS1u4RIS6bzTJph4wflpaWeM7d7/dRKBRYfkNMbNJSU5tTLBYzG5Ra2he5ao4ctkgSQbPPfr+PWCyGcDiMcDiMfD5/IdcHnPJS3ZOMqyehNfa6EIlE0Gg0sFqtWFlZ4WoiFovxQlYCuduT08HLIFxkSq0rqgSFWh4aFD969IjbyZMAykQ1Gg2zYY1GI7cb9/f3USqVvpNpUjuIxLxUqZx2m1AYBIVGBUQhpyqh2+0il8vxphHhTIY0coPBANlslkXYNLsQvridTof9R3d3d7Gzs8Pyi2q1eqbZLB2upVIJWq0WH330EQwGAzu+kNcmaWnJDYaMKkhmIFwvRLMmciza2dnB3t7ehaxZokQ6l8vBarWi0+nAbDYfEYpTIkCdFpPJBODF/XY4HFAoFPB4PPz/KRkNh8MoFApYX1/HwcHBmc6f6JmsVCoQiUTY29vjeR4FQZr9k61jMplk8TtJv8jjlaQg1WqVl81SEDwJtCLsokGzUa1We2SrEPAtwTCdTiOTyVzo9Z662eFlCnpCCNtiNpsNMzMz/LIJxdfvAjpEhdkZPSi0/0x4SB3XF14EaCMGbX8mDRmtCyL5Cx2aFPwUCgXMZjNvDaG2Oc1RTwPUjm+1WhwY6MAUiUQsBP/1r3+NXC7H5uzEIB6NRtyioaqq0Wjw3JbMEOhwzufzSKfT7Dv68OFD7gYQSeUsQSt7aH9cLpeD3+/HrVu3uNVut9shlUrZaYlWdpE8gBxtOp0Os7O3trYQiUSwu7vLJJGLeu4KhQL+9m//FrlcDlqtFnNzc3C73fxeUGdBp9OxcQElVjQ/o6BBi51TqRSePHmCg4MDfPXVV/wZzxJCl6LPP/8cMpmMFwtQAkIzQWKq0hlEXQxhQkP3i0hX7Xb7TK//XUF6Wr/fj+XlZbz33nvweDxQqVTMs6BuSj6fv9DPc/GOvxMCqlqoKtNoNCy1oGzyXQIhBQehvdpxG6RJtEojOQdJI8jRnqopIaWdDigKRkSHttlsaDQaaDabSCaTpxoESQaRyWSYbk7aLxLj+v1+9hMtFAowmUx8/YFAAHa7HcFgkNtU1PqkJKTb7aLdbrPGNRwOIxKJIBqNMuHmPCAkkHS7XZ5Pkn2bwWBgOYfQzk9oVNFut3m7C9nHkX6M5pkX+fx1u13eIB+LxdiWjjwxiVRBkiOFQsEyByJW0DaTYrHIWuT9/X2WaJ1X1UGBkNqi3wci0gjPHXoG6V0TWqBNKohoRoQYl8sFm83Ga+RoVR5tBqEz5KIwDYL/BlrE6nQ62YyXCA+04JJ67m8jsqYtGktLSzxXo4ydKploNIpSqXTuBJNXgQ4cMuM9bkwtBC3XvXv3LgKBAD755BOuqqLRKJtXl0qlU7m2fr+PcDjMgejDDz/EZ599xvss6Xv3er1wuVyYm5vjlj3dQ6GlH1X9VHGQicP+/j5yuRz++Mc/IhaL4eHDh6jVamg0Guc+NxuPx2i1WkyRp0rH7/fD5/Nhbm4OFosFDoeDBeJUCa6vr2N7e5vJW5VKhUkZNNs+L7/Gl4HIIo8ePUI2m2UW6/LyMmw2G6+tcrvd3Abf3t5GLBZjicfm5iYKhQIODg5QrVa5WqdkZlJBibLL5cKNGzd4MQAlx+SeM0mkueMguUcgEEAwGMR/+2//DcFgEC6XC8ALouGDBw8QiUTw6NEj9nO+yM8zDYL/BmoVVSoV9n8k493Z2Vm2ZyLiy5vcNKLVLy0tYW5u7ojZOFWZVHEJ26GTgOPsS+HPk2sFwWKxwGAwYHl5GV6vFz6fjz8TSWlOM+OjrL9arSKZTCKbzaJcLjPZha6T5jDU2hTeO+E9oP8mSQwZYO/s7CCXyyEcDh+Rg1ykHRq1Rkk3Rn6bNMeuVqtQKBRcMcnlcuzu7mJ3d5cXVzebTfbYPGkrwUV9tuFwyGQRSkaAb3W0er0e8Xicf+3Ozg7S6TR/hr29PVQqFcTjcbRaLTZwmLSNLCeBWthCWzF6hikRValULJqfJAj9dZ1OJzweD/x+P2w2G+RyOZuh07Jpki9ddOdrGgT/DZT1P3z4EJFIBKPRCMvLy/izP/sz/OQnP0G9Xscf/vAHHB4evrG7fiAQwE9/+lPWadEqG3rAiYxDbERiIU7KjrPjbVsAXNl+8MEHrP8JBAIso1Cr1dDr9SiVSjg8PMQXX3yBR48eoVgsntp1kVNGuVxGOByG0+nE7Ows9Ho9W9MdD3Df9+fRLr6NjQ1sbW0hlUphd3cXlUqFs1ahZvSiQDINkjcUCgWo1WocHBzwRnKi5FM1H41GkUwm2WCanq+L/izHQdUuJU4ymQzPnz/njgQFdQJVeVQxkZ8mBfVJGzG8CiKRiDtSx42zA4EAms0m3G430un0RNks0ntmNBphNptx+/ZtzM/PY3V1lVv0xEJ+8OAB9vb2EIvFWON6kZgGwX8DHYDNZhNSqRTJZBJWqxWDwYANk69duwan0/nG8gWbzYZgMAi9Xs+booXrd2izvFDMetEPBoGybZIWkECZtoTcvn2bV9IQmUQul/M6nmQyif39fd4ucdrZK7WJ6vU64vE4njx5Ao1Gg9FoBJPJxKJjmsOSvR7NkYRs1V6vh0ajga2tLTx79oxnSLSih9quk3R/gG8DYqvVQrFYRL1eR7VaPWKXRtZutGB6UkwNXgZ67oSSD7Lpo1kn4XhAp9ngJN6r14GQgyCU/AiJQZPSKSKQvZ3L5YLL5cLs7Cx8Ph+TlGq1GqLRKHtGFwqFC58FEqZBUAAKgsPhEIeHh7Db7eh0OrBarTCbzdDr9W/lM0huK9SWEz7gwrZWoVDg9S+T8vLS3OX4UF4mk8Hv9+MXv/gFLzumwTcJdNfW1rC/v49nz55hf3//nfc5ngQ69GgrdaPRgFqtRr/fRygU4uBMs4per8d7y+r1OlcQ4/GYW3Bk45TNZnn2R4nApIKqwoue6Z0W6PknGYNwC8aPAceD3GkR9M4K5IUcCoUQDAaxurrKmz5omfX29jYePXrE2trz2Br/OpgGwWOgDLJWqyGTyWBzcxNzc3O8N064lul1tHzCFSnC1tx4PGbro93dXUQiEXzzzTfY2dk5M8eRt0Gn02F7tG63C7fbDYfDgZmZGR7iU2AnyyvyKnzy5AmSySQikQg7ypzFQ0+VULlc5sF7Pp9HKBTiRcjk1E/MtFQqxW4dVBURSSSRSPBqr06nM9FEhCmmmATQSGd2dhbz8/MsTyLTgG+++QbPnj3D9vY2CoXCRLRBCdMgeAzUhqG9h9FolL0/heJv4VxC2LL4vj+b/kkuD8VikQkL5ExzkTvojoOc9slCi0x4zWYze2wCYDu5fD6P3d1dJJNJbG5uolgsIpPJnGnrQ0imaLfb2Nvb471kBoMBxWKRnfqJFUnbq4V2eOQGQxshTtNUeYop3gTCs2ISK7/jEHrUejwe3rBCc93d3V0cHh6yt/IkLQmYBsETQG3ReDyOf/3Xf8XBwQEePnzIBINgMMhbqbVaLe9Q/L6HVbjuqVarYXt7m62cYrEY9vb2eL4xKVkSXQ8xI5vNJux2O5LJ5JEgCIB3gT1+/Jg3RVMb9by2EQyHQyQSCXajoEWelLx0Oh2WpDSbzSOBjmzd6D5Nyj2Y4scDInuVSiVmVgtXhE0qSONIm0qoO1Or1ZBIJPDkyRMkEgkeN00SJv/bvQDQYUh0XqoQqK3Z6/XYOYVYiES8OA6h6wuZiZNDP633SaVSyOfzTAWfJBDjjggViUQCrVaLyUK0TWE8HiMej6NSqfA6KfIzPO9gQmLp0WjE1Gyq4uke1Ov1I63QKaa4aNAcVOiARMGF5vFETJu0Z/Y4CYsIa7Vajbe5kK/upHVXpkHwBFBrbDAYoF6v4/DwkAOcRCLBzMwMzGYzdnd3uVV6nLF2EqgqIpp6JBJBrVZj9uEkg0S6sVgMyWQS29vbR2acwLfrYeifF/2wNxoNiEQi9nAEvj1oJoV4NMUUBKqednd38fnnn2NhYQF2u50djsLhMBKJBJscTCqomm21Wnj48CF2dnaY+X7RZ8JJmAbBV0C4tZ5AexI7nQ4zItPp9Bu1Q4kFms1meYnpJPXIXwZqNxJ1fdIxDXRTXCYQV6BQKGB7exvNZpPXMPV6PTZrn8TzotlsolAoYHNzE7VajTfLkGE5XfMkajZFr7ogkUg0WVc7QTjJQeX7IPyuhYPvKaaYYgrCcYcmGjdMegfjJAmH0Bf5IjEej196QE+D4BRTTDHFFD9ovCoITsbSuimmmGKKKaa4AExngqcEYkVptVqoVCr4/X6IxWLWq+VyOTbxnWKKKaaYYjIwDYKnBHJ6J/PmxcVFyGQypNNp5HI5VKtVJpZMMcUUUwDfcgnEYvHEz/x+qJgGwVMCLZ69evUqQqEQ/uN//I9QKpXY39/H5uYmOp0O8vk8SqXSRInhp5hiivMH6YoNBgM0Gg0CgQAajQYODw/R6XSOeNpOcbb4QQVBIaNKqF87D0Nq2nrtcDjg8/l4nRAA1Ot1mEwmtFot1Gq1iRS7TvHDgFQqhUQigUqlYqYebceYPnOTAzLeMBgMMBqNmJmZQblc5m3rZNj+Q79ntEiYzCzIh5jkaeQ3fJYdtEsfBIU748RiMS8SJcNrALw25yyNqTUaDRwOB27cuIEbN27AZrNBpVLBaDQCADY2NgCANxJMms5nissNOkzcbjfMZjM+/vhj6PV6yOVybGxs4P/9v//HhgdTXDyUSiW0Wi2uXr2KQCCAX//610ilUjAYDAiHwzg4OECtVpuIRcdnCZlMBofDAavVCp/PB5vNBqPRyAt4v/76a1SrVRQKhTO7hksVBI9XeiKRiBeHksee0WiERqOB3W7nX5vJZFCtVpHNZtHtds/koSLHGLlcDoVCwf8tkUigUCggl8t5h+BlMMSd4nJBJpNBoVDAZrPB6XRifn4eBoMBMpkMtVoNBoMBjUbjjXdhTnE2oESd7pfD4YBYLMbS0hLbFJIxxWVvi1KRQpUerZUTiURQKpXweDyw2+0IhUJwOp0wmUyo1WrsppXP59Htdnld2Gl/HxMfBIWCUeqjH/9CFQoFtFotNBoN5ubm4Ha7cevWLQ6UX375JQ4ODnD//n1UKhW02+1z/xyTugdsih8GtFotTCYTVldXMTs7i08//ZS7EABw//59JJNJZDKZidpS8mOFRqOByWTC4uIi5ufn4fV64XQ6Ybfb4XQ6oVQq8ejRIwBgHsFlBRUHJpMJer2eEzSxWAy1Wg2/3w+n04mZmRk4nU6YzWbUajVUKhVIJBJEo1GMx2NUKhWUSiXuaJxWIJzoIEjVHX2JNpsNGo0GFosFGo0GWq32yL9TJmwwGOD3+zno1Go16HQ6FAoFZDIZRCKRc20xtNttJJNJFItFtFqtS93eEC73PO6XSkmKRCJhH0SabVz2bPb7QEmaVqtlN33yim2322cuj5HL5dBqtbBarXA4HDAYDNBqtRgOhxwgS6XSRG4lfx3Qc6XRaKBSqWA2m9HpdLhtdhnbhkJnGBrlUGAUiUSoVqvo9/uo1+uXMgiKRCLI5XIO+D6fD06nEzdu3IDFYuFznazhLBYLj7FoSe/q6ipMJhPq9Tri8Th6vR4vHj+t+z3RQZAWoZJH58rKCmw2G5aWlmCxWGCz2eDz+WAymaBWq49UivSyj8djXv6aTqehVCoRi8XO9YVpNpsIh8PI5XJ8Ay8r6LA/vlMRePHg0s8Nh0O0221eXUQB8YcKas3bbDZOziqVCsrlMkqlErchzyoRoH1uDocDbrcbRqMRarUa3W6Xg2M2m+U21GUDPVc2mw0WiwXLy8solUpIpVJIJpNMNrus75ZIJOKzTq1WY2ZmBtFoFNVqFfF4HJ1O59IlkWKxGEqlEiaTCYFAACsrK5ibm8PHH38Mp9P50mdxNBrxd/Hee+/B5/Oh2+1CpVIhm80yp+K03qcLC4LUzrRardBoNPD7/VCr1TAYDJDL5ZDL5dDr9VCpVFAqlVAoFHA6ndBoNEw60Wg0/GuIVXScHToej6FWq6HX67llet6HgFwuh9Vq5YWuk+qm/iocNwOw2+3Q6XS8S1EsFsPtdkOn08HhcKDdbiMcDiMej2Nvbw/FYhH1ev0HGwhJI/rRRx/B4/HgypUrODg4wN7eHtbW1pDJZM6krUVVBEl0jEYjjEYjV+i0FozIYZftuSPQyGN+fh6hUAh//ud/jkwmg/39fXzxxRfo9XqoVquX9vMJIZfLIRKJ4Ha7EQqFEIlEIBaLUalULlUglEqlMJlMmJmZwd27d3H9+nUsLCzAZrNBqVSi1Wqh0+mgVCpxx4RYoVqtFkqlEk6nE1arFR9//DFEIhG2trbQ6XR4L+GlDILCl1apVMJut8NsNuPatWswGo3cD6fApVarebmkVquFTCbjioMqEmHwoy9lNBpxq4GySCKnnBVeZhYrk8mg0+mgVqshk8ku5cZyWkqr1+uh0+ng9XphsVjgcrmYADQ7O8tZX7PZhMFggEqlQrVa5Yf8MmfrrwI907Ozs5ibm8Pdu3eh0+kwHo+RTCZ5xnHaoMqcuiXHEz3agtLpdJhyf5kOUoJUKuXzIhgM4r333kMqlYJKpcLe3h4ODw9Rr9cv+jJPBdTRMplMsNvtMBgMaLfbbLhxWSAWi7lomZ+fx8LCAhYXF9k0pFqt8jadZrOJarXKa9jMZjN0Oh3sdjvUajXm5uZweHgInU7HxMPTwrkFQQpGTqcTfr8fCwsLcLlc8Pv90Ov18Hq9UKlUHOiI7UaHL/1+CqI0a6IvkBhEvV6PW1N2ux0OhwPxeByZTAaHh4dIJpNncgj3ej20Wi3k83lks1ksLi7y/9NqtQiFQqhWq8jlcryr8DKASEhLS0twOp24e/cu7HY7FhYWeKkw8OL+UpBXKpUYDodwu91YWVnB8vIyvvnmG+zu7vKqlYuuCIVzTZFIxK2Vt7kuejZVKhXcbjccDge0Wi2cTifm5uawt7eHWq2GbDZ76p9DLpfDYDDA5/NhcXERs7OzbNlHBg3pdBqxWAyVSuXSVoOkI1Or1RzsZ2dn4fF4sLa2hu3tbZTLZXS73Yu+1FOBSCSC3+/HcDjE5uYmgBcs98t07+i9oARNJBKh0+mwbvXzzz9HIpHA48ePUa1WUSwWuUAIBAJwOBz4T//pP8Hj8WBhYYFb/kql8lRn2+cWBIWDX6/Xi/n5efj9frjdbia7yOVyqFQqriyokqPslbR1JKJst9tsSZZOp9Fut9Htdnkg2+v1IJVKUSwWUSwWOfM4i2xqNBpxIGw0GkceVqlUCp1OB5VKxQF90kFzVZVKBZVKBZ/PB6/Xi8XFRdjtdszNzUGlUkGtVvP9IR0mHUREYPD7/SxPyefzEIlERyjgFwGhnlQsFqPX6/HL+SagYErPrtFohE6n4/b8WYO6DGazGTabjbsn4/EYnU4HuVyOW9EkPL6MoGdM+MzQSIRIcUIewGUGfQYaDxED/jKCNsy3Wi1UKhWo1Wqu+vb393lcUqvVUCqVWBICgHev6nQ6llNYrVao1epTnW2fWxBUKpXw+Xy4cuUKPv74Y9y8eROBQICDHvBtS4n6wpVK5cjy2VarhW63y62lYrGIQqGAer2OUqmEXq+Hfr/PGcjCwgKWl5eRzWZRLpcRi8VQKBTOrBJsNptIp9MwGAxHxPByuRwWi4VL+e/bQD8JoDbG0tISAoEAPvroI7jdbiwsLECtVkOtVnOS0ul00Ol08I//+I/I5XJQq9XMVtTpdDCZTLh79y5u3LgBv9+PRCLBcpV8Pn+un4uClt/vh8PhwJUrVyCXyxGLxZBMJvHw4cM3OkSJ4eb1ejE3N4fr16/DaDRCLBYjnU7j0aNH2NvbQzweR7/fP/XPYzKZcOPGDdy8eRO3bt2C1WqFTCZDoVBAIpHA//7f/xtbW1tIpVKXWizfbrchFosRiUSg1+tRqVSg0+mYLWowGI4wci8TTtIOE1FGrVazzvgyJM9C9Pt9FItF7OzsQCKRwGKxQK/XI5lMolwu4+nTp6jVaqhWq5zc0LvX7XbRaDSQzWZhMBgglUoxOzuLv/zLv+RkmljX74pzCYISiQRqtRoulwsulwtOpxNarRZSqZQHnK1Wi38diSIpg02n01xhdbtdVCoVDoLVapX/32AwwGAw4DkJEWrK5TLq9TqazSa63e6ZVYKDwQDdbvc7TC6apVFwuAwPs06nQygUwtzcHEKhELxeLzMfZTIZz5nq9ToKhQLK5TK2trZQKBSgUqk4CDocDgDfVoVutxuj0QgajeZC9JpqtRo6nQ7BYJBbiMR0HY/HUCgUb8RklcvlzOabmZmBRqOBRCJh+n65XGYK/2knX1Sp22w22Gw2WK1WrhioIi+VSkyxv6xVIAAMBgMmv5TLZU6eKCEzm81QqVRot9vo9XqXsho8voz2+HLdywbqRpTLZcTjcVQqFahUKuRyOdTrdZTL5ZfOqoWVP/E7iBcil8tPVXd95kGQMhqr1Ypbt27h6tWrWFlZgVKpRKfTwd7eHiqVCpLJJDu+tNtt1Ot15PN5dg04HgSJaUkH1kkPfblcRjKZ5OBILKSzCoL9fh/NZvM77VCVSgWPx8OaxrMk55wWvF4vfvnLX2J5eZn789Qa7ff7KJfLiEaj2NjYwLNnz3BwcIBYLIZWq8XMX5VKhbm5Ody6dQvXrl2D3+/H4uIiDAYDHj58iFarde7tK4fDgaWlJXz66acsVBaLxdjb24PBYMA333zD2rPXuS6NRgOr1Ypf/epXWFxchF6vR6/XQ7FYRDabRSqVQrlcPnVpDI0XzGYzFhcXMTc3h5mZGd5GQEkKBcHLSogh0CwzlUpBo9FgbW0Ni4uLsFgscDgcWFhYQDQa5ZHERc+c3wTfd18u630bDAao1WpotVooFApM+CFOBCWGr/p89NwKpVmn3Uk789NYIpHAarXC7XZjdnYWNpsNUqmUA9yjR4+Qy+UQi8UgkUhgNBrRbDZRq9V4jkGiUeGXRxnEq2iyzWYTuVyO26vdbvfM2kEk3uz1ejz87ff7PBi22+1s6UaM1knKzIWZ1uzsLG7cuIH5+Xl4PB6YzWbIZDKMRiOUSiU0m00cHh7i4OAAT548wfb2NhKJBCclNE9UKBRwOBwYDoeQyWSctZOk5SLawqRbslqtzLwTiUQwmUw8fyFy1ateTiLVULuX3D4kEgm63S5LIhqNxpmwgeVyOc9p7XY7tFotZ8dEGut2u/wOXdaD9DjoXRbOjuh5u+yuTD+UeySEkJ1MVS3du9cJgMJ/P6vv58yDIDFCqfVEGqZ0Oo3Dw0Pcu3cPyWQS4XCYV4s0Gg1UKpV3Jk40m000m81T/DQvB5XuJAUgrztqyzqdTp4LUjk/KUFQ6Fhhs9nwySef4MqVK1hZWWGqMgX1fD6PYrGI9fV1bG9v4/79+4jFYt+Z7ZFLPjFBKcDSDOcsMrrXgUqlYlcVp9PJ7FaTycSkllarxd/Ly148IsPo9XpYrVZ4PB44HA5uhSaTSU70zqI9p1AoEAqFEAwG4XK5oNPp+JkiEhm1q1ut1qWvBAGwvOb4AUpVwmVvHR7/78t+v4Bvk5Y3LT7os5/0vZw2zjwIyuVyrK6uYmlpCQ6HA61WC5FIBE+fPsXOzg52dnbYUQMAV2uXbecekR7y+TwUCgWSySRkMhm8Xi8TddRqNVeDKpVqotxjqG1tt9vx6aefwuPxwGq1QiqVotfrIRaLoVwu4/nz58jn89jY2EAikUA0Gj2RUUnuKQ6HAy6XCyaTiedlFwEKWlqtloMdOaoIhf3VahWdTgfAq184ImOQ9slkMjHTtNFoYGtri+cgp02IIUbo0tISe+VqtVoA4Ky7WCxywvJDXKN00gxpih8GRCIRVCoV9Ho9W60BYJbpaSeV51IJejwedhNptVoolUpIp9OIx+MoFApHduxdNmYXgWaCNPAtFAowGo1wu91HiDoajQZKpRJyuZwD/0VDaCpArhwUtEg6kMvlkMlksLOzg2w2i729PRQKBZRKpRMfSKlUyrvSyMLrIklBVOkSrZ4MGIjVm81mUSgUXvslo4Dqcrng8/m4zU1SkVQqhVKpdCbru+hZcrlc3NIlQgwRSOr1Omq1Gs/RT/o8L7sXkx5QhIQJmhdRK/SyVoLAt2SYHzuEzFir1crdGqHpw2laEJ7bTJDYW9Q+8nq9R7QjZKlFA/DX6RlPEujFrNVqEIlE+Oqrr1AulzEzMwOVSsUaSSLI0KqQSRrgkzCeDvTBYIBUKoVsNot/+Zd/QTQaxYMHD1Cr1VAul1/JOFSpVJifn0cwGITT6eQFwxcFChrETqa2dDqdRjKZxO9//3uEw2EUi8XvtWMSiUTMfL169Sree+89aDQa9Pt9pFIptktLp9PMWj4t0OyWrOusViv0ej2TrYiVmkwmWTt7fHclOScRSYuC93A45K3mk2hITUlyuVzG7u4uLBYLRqMRrFYrZmdn2a/1sgaSy3rdpwki34VCIczOzmJ+fh42mw3Ai20a6+vrLJk7rS7auTrGkIhdr9fD5XId0fyR20O9XucWVa/XOzIAvwygTJxkHHTtxGyiCmRS3fypagVeMPJKpRKSySTi8ThisRibgFPL8GV/Bm3NJpOAi2TEEkmHyC8kZqe9bdSZKBQK39u6FNqUESmGHPFpZkrdjU6ncyZt/eMSIKEwnxJJmodTICPGLm1iIPcNcmaiuU2z2eTklEYTk5SIkgypXC7zrJOSa3q3JvG9muL7QYJ4nU7HxDWdTscOVER0pMTy0lSCw+EQmUyGCS+UQYdCIdb9tFotJJNJFAoFbG1tIRKJYHd3F+l0mq2eJulFfBVoeC/ceXUZ9T5UUTx8+BBff/01Hjx4gHw+/1om2MJWIa22Em6bOE9IJBJ2Kbp9+zauXLmCQCAAiUSCWq2G/f197O7uYmNjA9Vq9Xv/PHL/cTgcCAaDvAeu3++jUqngj3/8IzY3N1EoFHjme9rPLrEhhavGCP1+n2eCVBXRLJo2MLhcLmi1WthsNna6IVJXsVhEqVTiz5DJZCbG65bWczUaDUSjURSLRYxGIxgMBoxGIzbTv0zv2RQvQM802Wq+//77vHdQIpGgUqkgFovh4cOHSCQSRxK8d8WZB8F+v49oNAqRSASz2Qy73Q632810eTKUlkgk0Ov1AAC9Xg+DwYBEIsFav1arxQfwpLVpXobjDCcKDrQZY5JfVto8QK3PRqPxWi0IWpSp1+ths9l4tkhi9OM/zhJUkTocDni9XszOzsLtdsNgMPD8NplMIplMntg2POnPo/1nNpsNLpeLnXOo+kqlUlxR0hovCoRn+XmF9oL095CLv1qthtPp5IDt8XjYak1YCfZ6PTY+6PV60Gq1XB3W6/WJGE9Qkil0GLnsEomXOcZcxs/ytiDimsFg4HVgZLRBlX+lUuEOy6WaCbbbbfzhD3/A2toa1tfXsbKyglu3bmFlZYV9Q2lFz2AwwNzcHNrtNhqNBh8o//AP/4B4PI719XW2T5t0CAMgvbhkFG6z2Vg8OkkQvnhkSlAqlVAsFtlt5/sgkUjgcDjg9/uxsrICv98Pq9UK4LsH2FlXF0T0uXHjBpaXl/HZZ5/BYrHAarXi+fPnODw8xMOHDxEOh9FsNr93dke6wJmZGSwvL+PmzZswGAw8CybWbDqdZq2hUqnk2SkFxtPCy/6s8XjMDNLFxUVYrVYsLS3xjNbr9UKn00Gn03HwoPtSKpVQrVZht9sRi8Ugl8uRz+ext7fHWt1Jw3kmVmeFVwXCH0NApBm1z+fD8vIyrly5Ap/Ph2aziUqlgoODAyQSiTMhm515EByNRkwAITcLysI9Hg88Hg9XhXRoEYuPHGSy2SyTSYrFIhKJxES0Z94UNIchduKkPdindYgQW09ohN7r9djzL5vNolgsolarndmhJRaLuRq9cuUKr3mSSqW87YNmnZlM5ntfKrFYzAbZgUAAwWAQoVAICoWCdYGkl2y1WrwPTalUol6vo91uo1wun3kXQ2hSINzHNj8/zwQ1vV7Ps0Q6YOk+0bz0ypUrcLlckMlkODw8ZKuriw6CQiMGmjNTcnVZAyDw/TrBy/zZvg8kiTCbzazXJU/idDqNbDaLjY0NlmPReOzSVIKj0YgPgUajwXZopVIJXq8XV69ehdls5uzUbDbzB9TpdLweyel0sqtMKpW6lFmfUqlkVxLSlP0QQW4qwlVF1C7M5XJIp9O8/eMsQEHYYDDA6XTi2rVr8Hq9MJvNPOvMZDKIRqOIxWKvtaKGdqOZzWaEQiH2CqVtJrFYDJFIBPl8HqPRCEajEWazGWazGel0GtVq9VzYwLR3j+QTDocDVqsVoVDolc8bBUKNRsPbC3q9HsxmMzY3N/Hll19iMBhc+M4+ITGJnJeI2XrZzoTjFezxZ/CyV7evC/LAtVqtsFgsMJlMLDWi5HJtbQ3hcJhHYqdZBJ0LZY+8DNvtNgqFAtrtNjqdDu/3I7ao2WzG7Ows9Ho9TCYTZ6yBQABarRbvv/8+V4SlUgmFQuE8Lv/UoFQqYTQaYbVaYbPZoNPp+Hv5oUPIWqT54llpQok5effuXSwuLiIQCMBgMGAwGCAWi2F7extffvkltra2eNb1fZDL5ZiZmeHloDabjduIxAbudru4evUqTCYTrl27xpX+gwcPEIvFkEqlzrySIjbdzZs3MR6PWZMKgAku9HmFjivC6l1Ybc3MzKDVakGn06Fer1/oqiLSj5lMJiwtLcHlckEsFqPZbHLL/rKQ6BqNBiQSCba2tjAcDvHee+/xvfsxQaVSIRAIYH5+Hh988AGuX7+Oubk5jEYjZDIZ3L9/H5FIBI8ePeJtE6fdBTw33joFQpotDYdDpjlrtVrkcjlYLBb0+33Y7XbeBUhEBIlEgmAwiH6/D5vNxky2SXzghfZOQpC+i3ag0QE1id6Ox+cRb9K6FYqX6b9p5kRzpTfZ1PCm101LPOfn59nNhVZ0VatVDki5XI5//Unfv1CArdPp4Ha72R5Nq9UeIaMMBgOIxWIEAgG4XC7cunWLTd93dnagUChOvf190p+nUCigUCjYQYaeRZIWkOxB+HwK2aYku6BWtsViYeN3pVJ5xJrtvEGGDqSRJKs4socjq8LLAOHqNZ1Oh3a7zd/9q2aDkwjhey7sAAlx3OAA+HbE4Ha7EQqFcOXKFQSDQV6EXiwWEQ6HEYlEkEwmz4ylfO7iLSIIlMtlVKtVJogQo3Bra4sZpKurq7ynTaFQ4Pr169DpdEin0xgOh4jFYud9+d8L0gnmcjmYzWa0223I5XIWKKvVataW6fV6tNtt1Gq1i75sAEdfNiJW6PV6GI1GqFQqFlK/CuQVa7fbv7MMVNj2OSlJeNdrpwTjgw8+wMLCAj777DN4PB6YTCYAL8g+RqMRs7Oz0Gg0+MlPfsIBIpvNHgnKIpGIfy8xel0uF/R6PbObSX4gk8nw85//HK1WC9VqlfWv+/v72N/fx/r6OpNlzhuj0YhX2Tx58gQbGxuIxWKo1Wp8L+VyOex2O2ZnZ3H37l1cv34dJpOJ753BYMDHH3+Mra0ttNttVCqVN14+fFqgYE1JpEgkQqlUQjQaPZNtHWcFMiNIJBJQq9VotVrQaDRHXGNoTRe5LhGJ8FUa3fMGXSMx3mdnZ2E2mxEIBNgjmc64vb09xGIxtNttjMdjuN1uuN1u/Omf/ikCgQBWVlbQ6/VweHiIL774ApFIBN988w2KxSKbqJwFLkTBTJkzAD4YaDOESCRCq9VCq9ViJwyPx8MVIc1Z1Gr1hWalLwMdqvV6HfV6/cimC8qO5HI5V4Ek7p2Ez0BBikhMCoUCBoMBFouFZ7XCjfBCuzWqHGgZr9lshlKp/I5I/mXGuG8L4YyIpAuzs7NYWFjgzR0kzyD5htlshlwuR7fbhVQqxWAwgNls/k5lGgwGjxBJaCmyUPJBwVwmk7Fuj5aBZjIZXiB6Vofzy6oDqrwbjQZyuRwODg6ws7ODjY0NHB4eskcqyT6cTicGgwE8Hg9cLteRBEYqlcJisfDi2otmNQvbtgCOVIKXZWkw3R8694RtPgqE1AlTq9VciU9SpUvFi8PhgE6ng1arxdzcHL+DVNVS4kSSIRpBBAIBuN1urv50Oh2y2Syv1ovH47wK7CwTm4lZbNfv93n3VCKRgFwuZwGy1+uFTCaDx+NBq9WCy+WC0WhkjeEk6Qap1RSNRqFSqdBoNKBWq4/omWixK1UYFw1hhUZiZLVaDYvFwpvS7XY7crkcwuEw6wdpU4TD4YDZbOaD8ubNm3A4HLDb7WyXdhY0dqpY9Xo9gsEgrly5gvfeew9Xr16F1+tlhiSRJ5RKJa8dousgHd9JJtMGg4Et74QkH5FIxD6GwpVghUIBh4eHqFQqSCQSKBaLKBQKzKo8i+f0pO9yNBqx68uDBw+wsbGB3/72t8jlciziF7aWaMcbObCk02n89//+36HT6fj/07MqdKe5SAiDf61WQzabvVRroyjZpAXiJyXzGo0GwIvdnt1uF1arFSKR6MKqcCHIEWpxcRGfffYZG2PQwnRKPoFvXX7ee+89lMtlFItF9Pt93uJCLGuFQsFyiOfPn+Pg4IDNUs4SpxYEhZR44V6zV2X+wvYbHTKU/VDmrdPpjtiMHaffT1rmR8GEjKcHg8F32mxKpZJlIZMklRC6hozHY17aOhqN0Gw2YTKZIJfLWbtDrSmXywWLxcJzGr/fD6PRyDZWZ3UoCd3mPR4P/H4/ZmZm2FSarNHa7faRPZStVosPHZIJCLNv8s4UBkCqfojg02g0UKvVEIvFUCgUsLOzw/Kder3O9k4UcM4rAA6HQwwGA5TLZWSzWWxvb+Pg4ADpdBq1Wo2/C+GhK5wZkg5XmHmPx2N+li+y80L3R6lUMrGMKg2qbE9bi3neOD6SoM6DVquFVqvl2SHhLNuEL7s+uVwOjUaDmZkZzM7Osm8rvfPUzaOzmu4HkR31ej13X6jKpbihVCqh1WphNptRqVRYcnSWLeBTCYJUEahUKt4WQHvVhMNQ4cNJ2SRlljKZjL9ctVoNrVaLlZUVzM/Pc2vt+DCf1vxMGqjdS4tNhT53RLKwWq2wWq3MuLvo66XAXa1WsbOzg1AoBLPZDI/Hw+tM6vU6b48/HgTNZjMcDgfPdsmY+Sw/m0QiYXnNjRs3cPPmTbz//vvQaDSQy+V8sGez2SMMQmGbmua1ZrOZD5x8Po90Oo3l5WWMx+Mj2y86nQ4KhQJisRgODw/x5MkTJBIJhMNhNBoNnl9QRXLeB3Kv10O73UYkEsHBwQE+//xzZDIZxGKx7xATCMdNDI4biA+HQ9Tr9e9UkOcNSiAtFgtWV1eZMFetVpFKpTjIX+YgKAS1ns1mM2q1GqxWK0sH6Nkql8vnNiOkQoXY/H/yJ3+ChYUFfPDBB3yO5/N5lMtl1Go1jEYjHqtotVr4/X64XC60Wi0Mh0NOMClZHQ6H/Blv3rwJs9nM7xTJ4s4CpxIEyZ6JtscTkSKXyzGZ4vjLR5UcBU0yWrZYLNBqtdDr9ew2QjOcTqfDW+eJZTrJQ/B+v49CoQC1Ws1O6PQiU2Y3Ce1Q4Ntsv1qtYmNjA51Oh2eCpGuk9SbkT0nzOLp3VLULTRHoxTmrB5jmq7T5YjgcolAoYDAYoFgssi9to9HgViAJbkej0XeCoE6nY/kNLRQ2mUxcSZbLZezv72Nvbw/b29vY3NxEJpNhA3hK/C5K30UttkajgWq1ytvtX2XdRhm40WiEy+VCIBA48lzSbLHVal1YECTmKrFVqVUtbE0f77pcJpzExhbO3BUKBe/3FHYrzrpKEoIKnfn5eQQCAVy/fh12ux1yuZzXqkWjUVSrVdYAkxUaLRUXsrHpXKBVXyLRi+0sZNZAW0GSyeSRLsVpv1enEgRlMhnMZjMWFhbw8ccfw+v1wmg0Ynd3l3eaHdd3ECmElpHabDa2FdPpdOwaAHxbWdGC0Gq1ikajMVEsqeOgIJDP56HX6zkgkDCUgiCxDC8adL2VSgXPnz9Hu92GSqWCx+OB3W7n+Z5Go3np9VJbkQIMecLS3O20Qa0Zai8TySWXy6FSqSAcDrMkotFoIJ/PcxA8qRIkB/t6vY5qtYqFhQW4XC6WP1Cbc3d3F2tra3j69CnC4TBKpdKpf7a3BQVB+gzk+/qyNqZQdmCxWODxeHj9F/16qgQvMggSQcRms/GOOaogKCl71Wqvy4rjLWCNRgOj0ciBJpvNntu1UEW3tLSEhYUF3Lx5k7sk+XweOzs7bLxOK+VoYUK/38fMzAy/s8C3bfh2u82fU+hp6/P5UK1WYTKZmGB22r6hwCkFQYlEAq1WC6fTiYWFBaaW04c/ScBKFQJJB4gtSRm98KAlt41Hjx4hHA7j0aNHSCaTp3HpZwYK3JVKBfV6HYPBADKZ7KIv65Wgw25tbQ3JZBLhcBgzMzPwer1YXV2F1WqF2+3m1jVlpcCLz0tiZWqFjMdjaDQaNqw+bZAbUT6fx+7uLrdOyOZra2uLA0G/32fPQeFs6/hzqFAoYLPZuLVLa1zq9Tp2d3cRDofx5ZdfIhwOcwt0kkDvEm22+PTTT5FIJLCzs8P6TGpdERnBbrfD6/XiypUruHXrFubn56FWqzEcDlGpVJDJZJBKpVAsFnmmeFGgmSztIf0hiMuFtm8nHe607UMsFrPcJZPJYH19/cxcl4Sg5N1iscDpdOKnP/0pgsEgDAYDSqUS9vf38fXXX+Pp06dsbUajMWIU6/V6yOVyjMdjZvKWSiVeaC1cd0amAXq9Hh988AEcDgcymQz29/d5iffEBUGa6ZEGjmQMpM96WXZ2UkUhnE9Rn5gYRXt7e4hEIkgkEqhUKqdx6WcGYn+1Wq0T28GTCGpNZDIZduVpNBool8tQKpVoNptMRlGr1ezxSveMhtjlchmj0Yjb5HK5/MyIIZ1OB7VaDalUCt1uF81mE+FwGNlsFpubm8w4fp0Xh4IhteNVKhVfe7vdRjqdRjweRzgcRjKZvPAKUHh4EmhOazQa0ev1sLy8DLlcjmw2y6MJmtlrNBpoNBoEg0H4/X4sLS3B5/PBZrNBKpVyECyXy1xRXlQlKBT9k9CckpZJf69eBSE5SXgvhbIprVbLHAqlUolqtYp+v39uVSDN7ahKm5mZgc/nY9/caDTKM+hMJoNer8fMbKE5CD1TjUYDjUYD8XgctVoNiUSCO2QOh4ODLXWiSFNYLBZZFneaOJUgOBgMeOYSjUaZ1Uml8knBjtqj7Xab23ClUgm7u7sAXnzx2WwW1WqVmW2RSAS1Wg3pdPrMLLdOC1QJ0pD4srVqiGnXaDSwvb2Nx48fQ61Ww+12s+Dc4XAgEAgwAeU3v/kNEokE741cXFzE8vIyk1VoXihkEL/LAUbzP5obEBmHnEOO669eBWoJ2mw23L59G3/xF3+B5eVl2Gw2ZDIZpNNp3Lt3D+FwGFtbWxf6/AnlGUajEfV6nd1GyFNzYWEBwWAQCwsL2NzchE6nQ7PZ5DY3zWr0ej1bkC0uLvKYglaX/eEPf8Du7i7T1S9KgkD3MhqNwmAwIJPJAAA741xWUGVbrVah0+kwGo2O6DDFYjEsFgu747RarXNnhFKHzuv1YmZmBk6nE3q9Hs1mEwcHB/jNb36DZDLJrUu1Wo33338fXq8XP/vZz1i/KxKJkM1m8eDBA8Tjcfz+979HqVRCLpfjStDn88HlcuH999/n3YIAEAgEkE6nz2Rd1qkEwdFoxKSBZDIJo9EIAMz+ETrVU/uJZjKk7SkUCkw1B17c/HQ6jXK5zNvMiWhDL8QkgypB2sIuzPKINUrm4JMIykzJ6o6cbxqNBrc3yfaOsvOdnR0kEgm0220YjUaYTCa4XC50Oh0WmNNmBTqs3/XzDwYDDgpvC6oAdTodvF4vfD4f/H4/DAYDZDIZ6vU6SqUSG79fpCsJPVckZSGGMX0Ges/IwYO2WMzPz7Nfq0qlYn2lVqtFIBCA1WqF0WjkdnG9Xmfbqmg0euEavOPiciHr+rhN32UBJcqdTgfZbBZqtRp+v/8737FMJjvy+SuVyrn6DdP3S5INMseg66lWqxiNRiycpyTZ6/XC7/dDpVJBpVLxrsrDw0NEo1GEw2EufujPp8TbbDaj1WpBqVTyWrKzur+nEgR7vR7S6TT6/T5SqRR/ERQEAbDjC5XHnU4HvV4PmUyGSQvktAGARaHEgKKD9rTtts4K1FpMJBJwuVzodrssHM/n84jFYohGo6+1weAiQW3EVqvFm0AkEgl2dna48qJf02g0uOKl+0eVPvX7A4EAhsMhfD4fZDLZhc92aSBvtVqxvLyM//Jf/guWl5exvLwM4MWzTWzQaDTKWyIuEhQA7927h3K5DIPBgJmZGTYGEIrZZTIZ5ubm4HK5jvwcVeTCACJ0OlpbW0M0GsXf/M3fIJPJ8EE3CSAyDCXC1BYVHs6XAePxGLVaDdFoFH/913+NDz74ACsrK9yuJohEIvT7fezv72NtbQ3/8i//glQqda7XORqNmKFJs2WSD5lMJni9XqjVaty6dQtutxtXrlyBVquFwWDg1WVff/01nj17hkePHnF3hf4sQqVSwc7ODiKRCMxmM+7evQuVSsVjsbNgXZ9aJUiECNoDlc/nj+irKAgSk49aVrlcDu12G6VSibMKAPznkKPCSfqlSYawHZpKpbC9vc2ZN1VMxKK6DJ9J6PZC1QIdoAR6MYghSo4p5KNKLXLyGqTn4yI/P12Py+WC1+vlqkgmk6FUKqFSqSAWiyEej6NSqUzEQmdKsGgDC3VfrFYru7oITY3Ja5MgNJ4QOgXR/rZ8Po+1tTVEIhGUSqUj5gIXieOuRkStJxKFQqE49YWrZw2hljWTySCbzcJgMMBgMPDnJakL8SHK5fK5VoLUeajVaiiXy6jX61Cr1UyWWV1dhU6ng0ajwdzcHKxWK8ulaEwWiUSws7ODnZ0dZDIZdoI5SZNKAW8wGGB3d5ft13K53JnEgFNth3Y6HRSLxSNekvwX/dvmYHKDoYO0Vqsxc++yVHmvA/pODg8POduhNiAdqAcHByfadU0yKMh9331qtVrY399nbRfZxJEWj7wQLxJE4bZYLLhx4wauXbuGGzducEUVj8dxcHCAr7/+mtd+TYJ3I1Xm6+vrR0gIZG9HBxQFQuG7KCTT0LyUgkqhUMDz58+xvb2N//N//g8ikci5z5++D/1+H61WC5lMBhaLBePxmA0TYrEYv2uTdM2vwmAwQKvVQiwWg8lkwrNnzzAzMwOFQsEjk7W1NaRSKfzxj39EIpFALpc71zEKjW3i8TiGwyEymQwUCgU8Hg8WFhZgtVpZ7iWUKtHn2tvbw5dffon79+9jfX2d29ivukeVSgXVahW5XI5/jmLGRAZBIejlon8SSMhKAZJeRFqrNAmZ5mmCPn+j0eCtF2T/RhZPtVrt0uw/e1NQEkASBiIIqdVq2O12rK6uQqlUIp1OcwJ1nqCZ2eLiItxuNz744AMEg0E2je52u0ilUgiHwygWi7zMc9LuVaVSwdraGkQiEer1OlZXV3mZLpFcTvo9tNuTWlWlUomdb8j39CwOnHcBdRhqtRoODw/hcDgwGo2gUCig1+vZpu8yQcgiz2Qy+Oabb5BMJhGJRFhetru7y760pVLpQvyS6bsnb2elUgmv18v6UoVCAblczmzscDiMcrmM3d1dJJNJ7OzsIJfLvbb1npA/QcncWcWIMzHQfllFN+mMztOGkA6cTqcv+nLOFRQEa7UaH7L1eh0+nw8ajQZXr16FVCrF06dPIRKJzr3iIA3T0tISZmdn8eGHH7Kcg1qDqVQKBwcHbII9iUGwXC5jbW0NrVaL5+kzMzNMSz/e+hyPxyiVSqzvKpVK3KLa39/nhGUSqylhECQN62AwgFKpZD3aWVv1nTboOyYJzv3793npNo2C4vE46vU6EonEhZoCkDQlkUjw2icyq6DnrFQqIZvN4osvvkA6ncbz589RrVZZPvUmwft4IXVWmJgtElP88ECHFrn8lMtleL1eaDQaHpyXy2VsbW3h0aNHbNJ8liBCCDHXPv74YwSDQdjtdm7THx4eYmdnB48fP8bW1hazYCctAALgKoI0V0SUsdlsvN4JwJEgSJ0ImsMT45VmTZMYAAnEWKaZIADeD9npdNgYgIwTyGprkkGcinK5jO3tbR4ZUcuQiIE077yorhkxU7/88kvWbJPxAiUe2WyWdwcK9buTPKudBsEpzhREARcaV4tEIthsNgyHQywsLKBcLkMmkzHZ5ixfcJIQGAwGOBwOForT2pput8vWaPF4HLlcju3CJhE00yPSTr1eh1wuh0qlOiJPIlBiQmQH+ifJdl5XV3lREMoKiGFOC4Dn5+fZ1KFUKl24u82bQMirmFTQO3B4eMj6XOHsGQCbmJOcrVqtTvwzNQ2CU5wp6IXY2tpCs9kEALhcLszOzrJQOx6P86z4rIMNBQVawWQ2m2EwGJjUtb6+jgcPHuCLL77A4eEhisXixOtSKbARweyk4Hf817/qx6SCAmCr1UIqlcLW1ha++OILzMzMwGaz4YMPPsDCwgLG4zGi0ShSqdSFLwD+IYF4HalUCmKxGNFoFMC3zl9UuVK1ftwFZ1IxDYJTnClIbJ/P5yEWi9nT0mKxMNuLAsx5vCx00BM1vV6vo1KpYDQaIZvNIhKJIBaLsXXcpG8qIbwua/eyQ2jgQNR72mFHlazwu5j0A/iygRIuABNdtb4JpkFwijMFuc2Q/2g6nYbdbkexWGT3+f39/XOrtigA0n6yv//7v4fBYMBwOEQul8Pjx4+RTCaP7N+bYnJAou1SqYTnz5+jUqng0aNHsFgsTGra3d1FsVjk2ecUU7wK0yA4xZlDaIhORs6PHz9mWn8qlTq3reVUIZAB+/Pnz6FWq1mUnE6nUa1WJ04eMMULCI206/U6MpkMm0nTPklyoSJrtSmmeBVEr3rRRSLR9BSYYoopppjiUmM8Hr9UNyN+2f+YYooppphiih86pkFwiimmmGKKHy2mM8FzAG0qIH89AumYyDd1kmn4U0wxxRQ/RFyqICiVfnu5l8Vsm7Yyk7UT7Vqk1UNEwSeXjikZY4opppji/HApgqBYLIZSqcTCwgJ7A2YyGaRSqYn0cwS+XWFjsVhgt9uxuLgIp9MJh8MB4EUQr9VqqNVq2N7eRrFY5IW0PzaP1SmmmGKKi8JEB0HaRK9SqaDVamG32yGRSDAYDHjv4KRCIpFAoVDAbDbD7XZjaWkJDocDdrsdwIsgWK/XUa1W0Ww2eYM5gHOTC0wxxY8BNI6QSCSQy+W8A5OkFgQybqAO01m9f8JFxm9q9i00AZieD6eDiQ6CWq0WGo0GMzMzMJvNWFpa4m30hULhoi/vpRCJRGzJdefOHVy7dg2//vWveakucHTprtvtxv7+PuRyOWKxGJLJJBqNxsT6VU4xxWWBRCKBVCqF3W6HwWCAz+eDWq2GSCTizQ2EQqGARqPBs3qh+8xpQSqV8niEDM5fJxAKnY46nQ7v+Jvi3TFxQZBmaHK5HFarFSaTCTMzMzAYDJDJZGi327wPbVIzIZFIBJ1OB4vFAr/fD5fLxZuvRSIRZ5oymQxqtRpOpxOdTgczMzNsaExekFNMBkQiEeRyORt8k+XbFJMJMkpXq9XQ6/UIBAJwOByYn5+HVquFWCxGo9HgGT0ApNNplMtlFAoFtNttXp/1LvdZJBJBoVDw9hKlUgmlUsn7D2mB8+uASHTkhnPZgiBVvkqlkhMBqohpo7ww+QC+3fpCZ6fQp7Tf7x/ZrvG2xMKJCoIUAHU6HYxGI+bn5+FyuXDnzh0olUqEw2HU63VEIhGUSqWJbRmSR2YoFMLNmzfh8/mg1Wr5hlFwU6lUkMvlmJmZgU6ng0KhgEqlgkgkQqVSYcPpKS4W1E4zGAwcBJvN5jQITjCIR2C32+H3+3Hr1i3Mzs7i1q1bMBqNEIvFqFQq2N7exng8hkgkQiQSQTabxdbWForFIqLR6Du7zkgkEhiNRt67p9frYTAY4HQ6+d+FhL+XgeziisUi9vf3EY1GUavV3vq6LgJ0vlutVmg0GrhcLq6EaWFvs9lEp9NBv9/HeDzm5dcWi4XHY8CLIEibU5LJJDqdzluvzJqYIEj9er1eD7/fj9nZWfj9flgsFq4AE4kEkskkZ2qTGAApA9VqtTAYDLyotVKp8I9ms4nRaIRgMHjkJi8sLPCv2dzcvOiP8kYQi8XQarW85ZsyPFqjRISfyygDUavV0Gg0WFhYgFgsZu9R2n84ic/hjxUU/NRqNRwOBxYWFnDjxg1cuXIFXq8XDocDCoUCg8EABoMBs7Oz3Gp0uVzodDowGo1IJBJotVqoVCpvbaKuUCig1WqxvLwMrVYLs9kMo9HIPAGj0Qij0fjaQbDZbPJmjG63i3w+fyFb5t8EVMlJJBJoNBqoVCpcu3YNTqcT165dg0qlgkQiQbPZRLFY5Cq31WphNBrBaDTyfZLJZJDL5QBefB/RaBTFYhEPHz5EqVRCMpnkRcRvgokJgmKxGHK5HEajEYFAAO+99x4cDgd0Oh0v+0wmk0ilUigWixd9uS8FDb01Gg10Oh30ej2kUikqlQoSiQTS6TSKxSKGwyEUCgUsFgu8Xi+USiWMRiMymQyy2SyUSuVFf5TXBn1mg8EAnU4Hj8cDmUzG2XYul0OpVLqUhB+RSAS1Wg2TyYT5+XmIxWJuV+dyuam+c4JACahGo4HJZEIgEMDq6ip+8pOfYHZ2Fna7nYkl7XYbUqkUGo2G7yElrMPhEGazGTs7OxgOhyiVSm+855KCsV6vx8LCAiwWC9xuNywWC6xWK7xeLwdEWnz8KpBXajgcRqVSQTabxd7eHr9PkygXow6KVCqFQqGAwWCAwWDA6uoq5ubm8Nlnn0Gn0/H5SOd7Pp9HtVrFaDSCw+GA1WrFzZs3uX0MvAiCz58/RzKZ5N8rXAr9JpiIIEgPrsPhwJ07d3Dnzh387Gc/Q6VSQbVaxdraGuLxOHZ2dphBOalQKpXMZDWZTGi32wiHw/jqq6+Y9NLtdiGRSBCPx+H3+/GrX/0KCoUCUqkUtVqNDZwvC+ghv3PnDkKhEH7yk59Ao9FAKpVib28PDx8+xNOnTxEOh1Gr1Sb6swnnMyRzuX37NoLBIP7kT/4Eo9EIhUIBSqUS3W4X6XQajUbjlX8mHVBCVt95sPvo+jUaDcxmMx8ig8EAg8GAq5x6vX5kpdVlBM2a9Ho9PvvsM/j9fnzwwQdwuVzwer1Qq9UYDAZIp9Oo1WoIh8NHdjC2Wi38/Oc/x+LiIq5fvw673Y719XUolUrk8/k3IqJQV+vatWsIBoP41a9+BavVCofDAaVSCYVCAaVSCblc/tJ9h9SiJRBL3mq1Ynl5GY1GA71eD7u7u9wZm6QEk4oam80Gs9kMr9cLt9sNu92OX/ziF/D5fLDb7byZXi6XQ6fTIRgM8n0Zj8dQKBTcIaSKkhKS5eVl7hbSSq3Dw0Nsb2+/0bVeeBCkKoKy7VAoBL/fD4/Hw200Wm1TKpUmXkMnkUggk8l43tfpdJDNZvHkyRPEYjGkUimMRiPI5XJYLBaWSgyHQ/71l6ltSNm3TCaDz+fD0tISbt26Ba1Wy+w32tMnpKdPIqh1Q61cGsj7fD7Mzs5ifn4ew+EQGo0G2WwW8Xgc/X7/e9tZVAGTIQJR88+S+CQkFOj1eiZnabVa9Ho99Ho9SKVSNJtNfqcuyzN3HMIzxGg0YnFxETMzM7hx4waPG2jmRJ2knZ0d3kzfarXQaDRw9epVzM7OwmazQSKRwG63o1KpQC6Xv1HiRu+Dy+VCIBDA7OwsLBYLbDYbxGLxa70DxxmjVFVRm9fn86FYLKJSqXALkALHJEAqlUKlUsFiscDlcmFubg4+nw9OpxMzMzNwOp1HmLFEEgS+TQCEyeJwOOR3kn6PxWLhOT3dr7fpEl54ECQN4OrqKq5du4b/+l//K1qtFp49e4bf/OY3ePbsGXZ2dlCr1TjbmWTQAVetVpHL5bCzs4PNzU08f/6cgzrw4kZTdjkcDrm332q10Gq1LsWBRA+fUA5y48YNbvHQwUSHr0qlmtggKJPJoFQqYTabodFooNVquZ390UcfMct3PB7DaDTCZDLh6tWrKJVKfE9fhlwuh1qthlgshlarhXq9jkKhgL29vVP/HBT8yKLP6/VicXERn376KX+Ger2Oer2Oe/fuIZFI4N69eyiXy8hkMqd+PecBtVoNtVqNTz75BHNzc/irv/orWCwWmEwmZDIZbG1t4cmTJwiHw9jY2OC5O7EQSUZx9+5dLC8v825Cv9+PdrsNm83G1darIByF6PV6zM3NYW5uDkajEWq1+p233BPJZnl5GU6nE3fu3MHt27dxeHiI//k//ycymQx6vd6FB0KpVIpgMAiPx4Nf/vKXmJmZwc2bN7mq+z4ykJAB2m630ev1UK1WoVKp+PdSMByNRkin00ilUigUCm9FJrzwIEjDY7fbDZfLBavVisPDQyQSCcTjcSQSCV6OOUnl/stAQbBSqXBbJJfLse6PGE9qtRoGgwF6vZ6HvZ1Oh39MerAHvm370IzDZrPBZDJxACTaMlGZJ+n+Ed2aKnaLxQKNRgO73c4BkH7Qc6lQKPj32mw2/n2vapONx2Po9Xo2d2g0GnwAn8VnksvlkMlksFqtMBqNWFpawvz8PGZnZ+HxeGC329FsNtFoNJBKpSASib73M0wqhCQ0mgGGQiHY7XZoNBqMx2PUajXE43Hs7+9jb28PkUgE9XqdiXXj8ZgToEqlgnK5DL1eDwDQaDTQaDSs6Xud66FZoFarhdVqhc1mg1KpZJMPavVRV+B1QX8uySx0Oh0AcHL5pqL7swIxQC0WC5xOJwKBAHw+H9xuN38/UqmUZRHHxwJUGFBxQDO+RqMBk8kErVZ7JJkgpraQVfqmuNAgKBaL+QD95JNPEAgEIBaLEY1G8Q//8A/Y3NxENptlHcikHKCvAi2PffbsGbPUSNdID8Ds7Czcbjc+/fRT7o1Xq1XE43HkcjnkcrmJb/sCL+afJpMJP//5z3H37l0sLCxwpkbVcD6fRzKZPEKOmQTI5XIoFAosLi7C7Xbjl7/8JUwmE2w2G1cWNNQ3m81QKBQcBOVyOVQqFWw2Gwf3l4Es/mq1Gmw2G5rNJqrVKp4+fYoHDx6c2jNNFaDJZILRaMTdu3cxMzODX//610zAEDowGY1GfPTRR/B6vcjn85BKpTg4ODiVazkvKBQKaDQaLC4uIhQK4ec//zlCoRCMRiMGgwEymQyeP3+Ozz//HBsbG0gkEixtEd4zSs729vaYvq9SqWA2m2GxWKDVankJ86sgFoshk8lgt9vh9Xpx8+ZNzM3NQa/XYzAYoFQqIZVK8fvwJlWLSqXCysoKLBYLgsEg66W3t7fx/PlzVKvViWiH0lx2dXUV8/PzuHr1Ks+jCdTebDQaPBagMUEkEkEqlUI8Hkez2Tyi91xaWuI5In3OwWCAQqGAfD6PWq2GTqfzxtd8YUFQ2MfX6/V8+FQqFeTzeaRSKdTrdQ4qF31zvw90SOp0OiiVSthsNtb96XQ6qNVqngesrKzwvMBqtfIDkU6nkc/nuc8/6aA5BRkDKBQKblP0ej3k83nk83luU0zCS0qg7N9ms8HlciEUCh2RtJCQl4JLv9/n+0KU+eFwiFqt9tKEhbLzYrHI9PZ2u41Go4FisXiqAZC6CtQqu337NrMR1Wo1dxvousRi8ZH55GXoPBDoYNTpdLDZbJidncXi4iLsdjt0Oh263S6q1Sq2trZwcHCAVCrFiejLkunxeIxer4dOp3OkTSokY7wOaMzRbrdRrVZRrVah1+vRbDYRiUQQjUYRDodRKBS+V9dG3QpyoKLuAz175B5D45NJeLcUCgXPZg0GAzQaDSePQmZuu93Gzs4Oj3/oM1GCUCgU0O/3YTKZoNfrj1SB9J3Qu0jnzKULgpQ1GY1G2Gw2+Hw+SKVSxGIxRCIR7O/vH2mDTjrohSTqs91u5yBIJT8dqAsLC7DZbFhYWIBUKkW1WkUmk8Hm5ibC4TCLPycdVNnSC0rOGMCLNVG7u7ss7C2Xy+h2uxPxogLgrR6BQADz8/NYXV1lneNxUW61WkW9XsfGxgYajQbK5TK3eiORCMrl8ol/Bx2czWYTvV7vSBB92e95U9Az5Xa7MTs7i3/37/4dFhYWsLq6CrVaza3pkw7xZrOJWq2Ger1+KZ43AlWzNpsNi4uLuHv3Lm7dugW/3w+FQoFyuYxwOIzPP/8cu7u72N3d5bPkVej3+xwEAXAAfNn3dxyUUNRqNchkMkQiEUilUpY+ffnll9je3sbW1tZrXQ/93WTE73K5WMJBYwYSmE9KEKQxj91uh81mg8FggFKpZMu3wWDAifHf/M3fIJ/Ps2SMkkoKinK5HNevX4fBYGDvZSGjttfrsWwkEokgl8tdriAol8uhVqthNpuZSNHpdBAOh5HJZCaucvg+kNh9ZWUFdrudRbnUBqAgKBaL4XA4WEw/Go1QqVS450/zQqJATzqoqjh+UAwGAzQaDTSbTbRarYkRlZMln8fjgdvtxvLyMoLBIM9+hJkmtW0ODw+RzWbxzTffoF6vHwmCqVTqe507aL5BGTtl8KcBoSh8dXWVZ38qlQpSqRSj0QjVahXZbJYrv0KhgHq9jp2dHWSzWRweHk609lYI2svp8/mwuLiI9957D6FQCCaTCaVSCZ1OB5ubmzg8PMTm5iYymQy33V4FsVgMi8UCn88HjUYDiUTC8/nXFaTT80JtvMePH6NYLEKhUKBYLCKZTCKbzaJQKLyyaqF3yuVywWAwwOVywW63w+fzsXPKpMwAj4MC087ODprNJhMfqRput9scsJ49e4ZyuYxarcbPpnCmTcYpPp8PLpcLOp0OEomEmda7u7uIx+M4PDxEJpO5fDNBCoLkmiCTyVCtVhGLxZDP53kgOgkH5+vAbDZjZmYG165dg8fjgdPp5BYpPbB0uNK8SSwWo9PpcIAUBkH6/5ehCqZqRPhiUou31Wqh0+lMzCxQ6NcaDAaZuk1VE0FoWByPxxGJRPDkyRPUajWUy2V+afP5/PfOdqidT4nAaT7TarUabrcbc3NzWFlZYY9Man8SSYuE38PhkLVlBwcHqNVqSCaTE6+/Bb7VPWq1Wvj9fiwsLOD69evw+XwwGAzY399HNpvFw4cPEY1Gsbe3x8/gq75zCjrk5EJU/W63yzKK1w2CwLfLstfX11EsFuF0OlGv1zkA0sF/UhudrkUikSAQCMBsNmN+fh4OhwMulwtms/m1K9OLQLfbRbPZxP7+PlfERqMRVqsVlUoFtVoNW1tbyOVy2Nzc5ESZ4HA42FCAOoRE6CJJBfkrh8Nh7O3tIZFIMI/ibd6tCw2CNC/TaDRMpNjd3WUnjssEMvqenZ2F1+vlbFIsFnMvnDSAg8GABaLj8ZizO6VSyUShZ8+eIZvNchtx0ldHCdHr9dBoNBCPx9mUeFKIPqSdIwcPr9cLl8t1hHFGw/pkMol8Po8vv/wSh4eH2NjYQKvVOsIsfJ0Dkl7M03ymKVuemZnB3bt3cfPmTayurkKn03GbtlAo4Ouvv0Yul8Ph4SEHbiJR0PwmFAqhVqtBqVSiWq1+r/j/IkAJZSgUgsfjwSeffIL5+XksLi5iOBwik8ngq6++QiQSYclHuVx+LRYmBR5yb9JoNEdmetTOfh2QsfNwOOTZH7E3W60W+v0+t6hfdh02mw12ux13797F/Pw8rl+/DpPJBI/Hw6SzZrPJwZRsGCcBrVYL3W4Xz58/h0ajQSqVgl6vh9Vq5dZ7LBZDrVZjljTNtJ1OJxYWFhAIBLC4uAiLxYJAIMDeqySJKBaLyOfzePDgAba3t3nrztsmlxcWBElQStqR4XCITqfDJILLti+LHA90Oh20Wi0LwykAUglPWSnR80lmYDAY2JKLDLQp8yFd16Q86AThXjRhdkqZGh2olBlPAmjGQm0aIi0JxblEkMhms0gkEohGo4jH4ygUChOxwoYqIrPZzBWt2+2G1WqFVCrldWPxeBwPHjxAsVhEJpM5Ij6WSCTw+XwcXBQKBbrdLrrd7kQGQblcDo1GA6fTCa/Xi1AoxP6b2WwWpVKJuQSxWIwp869zhtDzS88EadiIwPG6lSCB2qLVahXdbpfdTMizVPiuCP9JZ6LRaITb7UYoFMLs7CxCoRD0ej10Oh0GgwEnYjQ/m6RZO839ut0uu0NptVoUi0WuyrPZLDqdDo9RyJze4/EgFAqxvtJkMsFqtXISQWcoWTEmEgkkEgk0Go13Gi9caBAkFp5CoWBNSD6fR71en5ib+rpot9solUrI5XL8MAMvhu1UGSUSCaRSKQDgjI/mG2q1munYS0tLWFhYQD6fx/379xGLxfC73/0O3W53Ilij9MKqVCro9Xqep1HQ7/V6aDabR+Yfk3A/KQDS3IHukXA1UqfTQTqdRiKRwO9//3vs7Ozg2bNn7Fh/0YmISCRiW75PP/0UCwsL+OCDD5iGTuOE3/zmN4hGo/jiiy/Q6XRY6C0SibC4uAiHw4GPPvqIWXypVAobGxt4+PDhRO3qpGfN6/XC6XTiF7/4Bfx+P+7cuQORSIRarYaNjQ3s7u7i3r17iMfjPLN9nXslFotZakEVWq/X45VFpVLpnebz3W4X29vbbHlG7VVKRMgu0WAw8H0l45CbN2/C4/HAZDJBKpUycSQej+P58+dYW1tDOBxGNpudmCRTiMFgwEzPeDzOP086R7vdzprK2dlZ3LlzBwsLC/D5fCxLouBHs/h0Oo2NjQ0cHBxgZ2cHyWTynZPsCw2C5DkpdAa/bHRtQr1eRzqdxuHhIVqtFpMSaCZWrVaRTqeRzWYBgGcQer0e/X4fFosFUqkUMpkMer0eHo8HGo0GmUwGo9EIWq2WH4iLNswlaQRVVAqF4kiLh65PKJK/aAgrQHKwEbp4UPZaqVSQTqdxcHDApg3kaj8JLj4ikegIo9rlcvFqIMqyk8nkkWun+0C/n7oWdrudNxsQyWfSjNspabFarXC5XOw/qVarectDMplEOBxGsVjk6uN1K0AKRDqdjpMi2nxSr9e5hfm2955cTwAc4TnQ+0KSKofDAbPZjGAwiPn5eQSDQVitVjaYBsDJZS6XQyqVQiwWQ6VSmWgGvfC6hLpbrVaLUCh0xOw8FArB5XKxcQUZDNCoLJ1OY2dnBwcHB4hGo0dkL++CCwuClA2QuPe4cbFQyzQJVcT3YWdnB8ViEQ8ePODt8b1ej/WOuVzuO8GL9D937tzB/Pw8fvrTnyIYDMLr9TJ7UalUwuv1Yn19nR9+asld1PdCi0INBgO/vMetkCbtnhFV3ev1YmFhAQsLC5iZmYFGo4FYLEa9XkexWMT29ja++eYb/OEPf2C/2kmy65PJZLh+/Trm5+fx8ccfs39iOp1GOp3G73//e4TDYXz55ZdMwz9+L6xWK3w+H+bn53lxtUKhQD6fZyeSSYBIJILJZILZbMb777+P2dlZXLt2DVqtFuPxGNlsFhsbG/jnf/5nPHjwAKVS6Y0qNupm2Gw2zMzM8DmUTCbZr5gM0t+l0qA5YblcZp6AwWCASqVi8svVq1fZ9Jvs+ihQ0oy6VCohGo3i/v37+Prrr/H111+j1WpdeHv+JNDnpCKHWs0ajYa1rD/72c9gsVjgcDhYLy6TyfgcIc1lpVLB1tYWvvnmG/zd3/0dKpUKGo0GarXaqZyDF26bJvSJo1kZbR0WinmFAWTSDljgRfZYLpfZ+RwAu0TQbOEkNBoNxGIxDIdDSCQSZDIZBAIB+P1+Xi4cCATwySefIJfLMVMxkUicShb0NhAy2OihnWTaNjFyvV4vZmdnmUVpt9sBvLh3hUIByWQSW1tb3GIis4ZJet7EYjH8fj+CwSAbFFAFGIlEWDNFZI6Trl14/+iwehM93HmAOkXBYBCzs7NYXl7mbRDD4RCxWAx7e3t4/vw5B6o3eRdoFqVSqWAymeD1ernbkkqlcHh4yK38122tvgxUfZOFmkKhgM1mg16vx8rKCsxmM2ZnZ2G1WrkNSHwAagW2Wi32yMxms1wFTWIblJJkIvqRbpASLjIUDwQC0Ol0MBgMkMvlzKOgZ5DIhMRgps9Ou0nf1HruZbjwIHicOUftCa1Wy0GQBKzUSjivVTRvAhpW0+4x4Nu24Kuus9PpYHt7GwcHB3jw4AFmZ2cRDAbxZ3/2Z5ibm8P169fhdDrh9/tRLBZxeHiIv/3bv8U///M/8wNxEaCDk+Zr5Ac4SfeEIBaLYTQacfPmTdy8eRMffvghfD4fjEYj6vU6qtUqwuEwdnZ28Nvf/hbxeBzRaHRitI1CUCVIrkPtdhuZTIZXVj18+BDxePy1SSHAdzcWXDSI+KNSqXDnzh189tlnuHnzJgwGA/r9Pms2nz59ij/+8Y+sBXwTEDvbZDLB5/NhdXUVFosFIpEI6+vrrDWs1WrvPIcXiUTQ6XRYWFiAyWRiJjnNZWksIrwPJKnp9/vIZDIsc4nFYgiHw7zeaRJBc2uj0cgV7tWrV9lU22azQaVSHdkicRx0vtfrdeTzeWxubmJ/fx/JZPLU38kLdYyheQwxQ0UiEbPcPB4PkxXC4TC7qhArijQ8k9KmEgbm4w/zq26acH42Ho+RyWQwGAxgsViYXm02m2G1WrlNHAqFeO8WgDc68E4D1N7pdDqcpbbb7Yky8iVIpVK2RSMxud1uh1gsRrPZxMHBAdLpNP7+7/8eiUQCkUgE1Wp1Yhw4hCBtLc00SVubyWTYk7Jer79UXytc80WH0LtuNjhtUAAMBoO4fv06bt68iVAoBJ1OB7FYjMPDQ0SjUTx58gQHBwcoFApvzAwUtvN9Ph+Wl5dx584dOByOI62404JEIoHZbMbt27fh9Xrh9XrZBsxkMkGpVH7HaKLf72N7exvpdBqbm5vsgkOJcKlUOrXrO01QC3RhYQFerxc/+9nP4HA4EAwGYTQaodfroVQqOWk+6bwQnqHHuSNEEDrNc//CvUMpCHS7XXZJuHbtGu7evcvV31dffYV0Os12QwCObGWYpMPqba5H2PYln021Wo1isQi/349+v8/b59VqNXw+H/x+/5HWwHkHQWJSUhDsdrtsmzZJ90MqlfL+tcXFRWaekediNBrF/v4+fve736FUKqFSqfD9mCTQwa1Wq3m7gVQqRb/fRy6XQzabRSaTYXeek0CHySQHQSIweb1e/PSnP8XKygpr97rdLm+E2NzcZA3qmz5v9F1qtVp4PB6eNdL3KcS7PMt0xpGc5dq1a5ibm8PCwsIRX1qhPIfOwk6ng62tLWxvb+PJkycoFouIx+PsPTsJJK2TQBV2KBTCwsIC7t69C5PJxInn8Zb7y9r1wj9PGASFjO7TOmcuLAhSgBuNRpBIJPD7/bDb7ewAn0gkOEuamZnh+QeVx+TcQVnRJPbG3wZkGH54eIhKpQKDwYCZmRmeIRiNRszOzqLdbqNQKLBw9jyH41QJtlotFuw2Go3vuK5MAlQqFT788EMsLi7C7/dDqVSiXC5jfX0dsVgM//RP/4REIoFMJsPLjCcpiAPfdk0WFhYQCoVgsVi46u52uygUCigUCigWiyc+B3T4uN1ueDwe3L59m7dyy+XyiWmrkRbQ6/XiypUreP/999nBhazryLiA5p5vk6xIJBJoNBqYzWb4/X7esFGtVlGpVHBwcMDdp7epMmlDyfXr19nfNBgM4sqVK3yOAS/eI3p3tre3kc1msbOzw2xeMg6hZJcIOpPYpifQuV6pVDipJAs/4CgHhL5b4Vz6eAA0Go0QiUT4+OOPodPp0O/3sbOzg3g8fmrfw4UGwcFgwBkNMYfG4zHr6YgdSi8HOQfQ5gKdTscP6iQ5qb8L6DMQ1TsajUIqlaJYLDK9mOYYJpMJGo3m3FuQpKujlijtSJu06gl4Uf04nU7eMEAzZvLM3NvbQzqdnuh1XdQ2EhqzC3eykYkyGSkf/720kdxut8Pv98Pr9cLtdnOLsdfrcaCkH+d9L6kNSpZ2TqcTLpcLKpUKo9GIxdGxWAypVIqlH28KagkTIYNWJ5FROmlbS6XSG+tyj4vuZ2dn4fP5cPPmTTaUVqlUAMBbE4iVvLu7i2g0iocPH7K9XS6XQ71ePxL8LpItf3wfIH0OoR0gnQ2tVguNRgP1eh0GgwG9Xo+fY6FZ9ng85jOduAVkGSms2N1uN3K5HJxOJxKJxKmeeRcWBEnzQlY6dDjFYjE8fPgQf/jDH9jV32AwsGaELK8CgQD0ej28Xi+SySQePnx4xIz1MoP0hb1eD3t7e+h0Onj06BGWlpZYJ6XRaOBwOBCPxy+spXV8Dnr8xySADld6waiFTkkYJWKTGPxeBuH3TtspKpUKzzIJwvnaBx98gNu3b+P69euYmZlhSQtp1mgPHOknz5N5TAer1WpFIBDAr371K1y9ehUmkwmxWAyZTAa//e1vEY1G8ezZM3ZiedP3XCQSsTbyk08+wczMDH7yk5+wo8lvfvMbJtxQVf0mfwdJAcjU+y/+4i/Ymo9E4b1eD+VymTWNm5ubSCaT+Kd/+icUCgWkUil+Fsli8aTlsxcBo9EIrVaLlZUV7kQUCgWEw2Eei1CAI4eie/fuweVyIZ1O855GSmL29vYwGo3YcIO2ujidTrjdbq4gqbIeDocoFApsW3hauPCZIEX8wWDA7Mp8Po90Os09YIvFwvMLciQnlwXyfdzb20O320W9Xn9nliK1NITOL8DR/rXQIkyYCQnF7G9yDSTcpbYAZUSU9QtF50JpwkkehGcN4ayDKN+vYnpdJEajEds1UVZP7TCj0QiHw8EZJx04VNnS/aP7e1FzGOGhSAcNPQsymYwp6G63mxMSyq5Ji7a0tIRgMAin0wmZTMafU2jXRfeSLNTOMwiSMTZ1OahFWavVkE6nmSJPW+HfNABSImS1WuFwOBAIBOB2u6HVatknNhqNIhKJ8IaHN32HhRZgNpsNDocDNpuNhfhSqZSrdlohdHh4iFQqxdtIhGbSdJ/f9iyj95TWgwHgmeObzL3pz9FqtTCbzQiFQiwnUavVqFarR/7c8XjMy6MTiQS36MmiMB6Po1KpYHd3F+PxGAaDgb8zvV7P23WAb4mDZMX4KunP2+LCxfKUXdRqNWSzWWxtbWFnZwfhcJi/UHqIlEolzGYzhsMhlEolv9wzMzOIRCIQiUQsmH2XL4kG8+SqQaBAJKy8Wq0Wz+aoDUDzstdlMdGhpdFouC1MLCqXywWr1crtPGHCQE4W550h0jJkqshJMP+yhOEi0e12sbm5CZFIhCtXrvALt7y8DIfDAZPJhHK5jHg8zoSEbDaLVCrF969SqXDn4qLaUaPRCJlMBhKJhNeMAS9c9z/77DOEQiF89NFHGI1GrCXUarW8VFc4SigWi+h2uzAajfxO0QFnMplgMBiOJA1nDWp5BQIBLCws4L333oNWq2UT6vv372NtbY09Qt8mOJPo/sMPP2TdLR3k+/v7ePDgAf74xz9iY2PjratgIQlG6G4j3CTTaDSQTCbx6NEjRCIRPHr0CPl8HoeHh6c+66MKKhgMwmAwAHjBJD84OOAR0pv+OX6/H7/61a9gMpkgEomwt7cHqVR65HsbDofsFVqr1fj5U6lUkMvlTP7LZDIAAL1eD6fTifn5eZjNZthsNuZ4EAGvWCxyS5w6h5eeGEMRXjjopXVCZDlGP082ZL1eDxKJBJVKhTMCcl4g/8rTaMVR1mOxWJg8IJPJ+EsX9sTJLq3f76Pf77OZK4lsX+dlos9NxBe9Xg+z2cxrckwmE0KhEKxWK8bjMSqVypFt2ed9KAvF1lSxHt/DNykYDAbIZDIwmUxIpVIYjUZHjJJp76HRaGQD6XQ6DZPJdOSFFhr/1uv1U6dpvwrUZWg2m6hUKigUCmwuLJFIYLVaMRqNoNFoOAg6nU6oVCo+/AAwoSyXy6Hf72N2dhZGo5ETGFqIarFYnQNHuAAAuJ9JREFUUCwWz02DSkb6tFuUHJeq1SoKhQIbF1AF+LrfO2mOVSoV/H4/nE4n71tUKpXs6LS3t4ft7e23aoEKQWcaebUeHxMA33Z8qHVKwYTcUSjBoerppHdJ2HU6HgzoPZRIJMwk9ng8sFqtAMCV9ZsEeeoomM1m2O12OJ1OmEwmAC+CusfjQSKROOJwQ9+jSCTi6peqcfJiHY/HfH6oVCouiGixgPCzHv+8P4hKUEisIHYaZVFE9hAOWQmDwYCz91arBafTyTZDWq32VNqDREDxer24evUq9Ho99Ho9t0iFmV2lUkEkEmErM7oueqGEldpJ1GB6YDUaDSwWC2w2G1sJ6XQ6JjD4fD6WJqRSKaytrXEgvIg23XHHGGFiMEno9Xo4ODiASCTC9vY2RqMRm0Y7HA54PB70+32+X91uF5lMBslkkhMxEiuvr6+jVCohFosdeW7PGnQA0B7DaDQKpVLJOytJW0tSGRIrE9mAbPtoqzmtKhOLxfB6vQgEArzJxOl0IhAIIB6Pn9v6LvLu9Hg8cLlc0Ov17OEai8UQiURQKpVOJP68DFSVmUwmOJ1O3LhxAzMzM7hz5w4Hfdr2vra2hvv37zPZ5m0PWHpe6vU6SqXSiX8WjTiIlENM79nZWdRqNfZ7rVQqJx72wuKBgqXwLKH3US6X867W5eVl+Hw+nqnt7++zH+frQKlU8paHYDCIYDAIk8nEfy/Zue3u7vJeSkooT9q1SWQt8oDV6XSwWq3w+/1wOBwwGo1HLBjpuz2r5PrCgmCtVoNYLOY25pUrV5hRtbGxwVn68Yee6Pm07uYs2oH9fp8H1FqtFl6vlzda03CX+v8mkwkOh4MfWCK0kJbnpDni8Z8TtkPVajX/IGGzVCrlOUW1WsXm5iYePXqEZDLJurbzhFAiQeuSWq0W1Gr1hcwoX4XxeIxGo4FsNotnz57xtTqdThgMBt5+AYDJC5Q904FTKpVQrVZhMBiQTCYhFotRKBSQz+fPzSBc+J0/ffqUZUG0Dup4hiwWi5mBR9Xf/v4+Dg8PWdPZaDQ4kFN1Qk4fxw+hswAlUtT5IDeR0WiEQqGA9fV1xONxZmq+jgxKLBbzO2qz2eD3+3nhMOkNe70eszG//vprJJPJU/GhJNOLUqmETCaDfD4PtVrN802pVAqNRgOXywWpVMp7HGlrRalUwt7eHstdTqp6R6MRt+aJWEjr18gfl9qP1PpfWFiA0+nkjfd6vf61W6HAiySFdgLabDa2NxuNRtytcjqdcDgcTOqjSk6YGNPMmZ61YDAIrVYLm82GQCCA1dVVNhKgzhsF/F6vd2YyuAsLgjRfSSQSzPzRaDRHdDtEmjleSVEVeVzXdVrBcDAYIJ/Pc4uJsipqMdHmdxJw0n8T+5AeVOE1E17WLhT6OJJnIB18g8GAD7NsNou9vT1sbm5ym+iigiC1fZvNJtrt9pGAMimgl7JYLGJnZ4dfpnq9DovFwiuIiC1JWSlV+xREKWs2Go0oFAoYDofnLqyndWPb29sol8tMiqG2qPC77/V6aLVavMA0n88jmUwik8nwFglK2Ki9LXSkOa8gSMklkZRMJhNXvbu7u0in06hWq6/Vpjz+59FGhmvXrmF2dhYOhwPtdhv1eh17e3vY39/H2trad7abvy2oc0Xfd6lUgsFggFqt5i4SGRUYjUYmfFC3K5fLQa/XI5vNIpvNnpjgEx+gUqmgXC6jUCig1WpxIu10OnnGZjAYoNfrEQwGYbPZuDrV6XSoVCqv/bmEEjVa60TPmkqlgt1uZwlIp9Ph8dHxs4DandT+Xl5ehl6vh91uh8fjwfz8PP8a4fdJG17OSh95YUGQAlgymYREIsHBwQFsNhv3m0OhEO8WpIBCpbNOp+PZWC6X4wWONDN41y+K9DudTgeVSgXb29v8YOl0OjgcDs7obDYb5ufnOesSPrjUlz8uHTjOIKWgQvMAuunkPF+r1XiD8tbWFou7ST903jM4YTZKVVKj0YBOp5s4BxLgxfW2222k02kWl29sbPDMjFx4iG1MLzslQJQEvf/++/D5fFCpVHj8+DFEIhFisdi5tQ2BF8/m/v4+0uk0KpUKZ/1CG0KSTrTbbfYRpSWz3W6XxfZCCDVg59Xapvd5bm4OMzMzWFpagslkQr/fRyKRwJdffolYLPZShxThfI26JhqNBjdu3IDH48H7778Pq9UKp9PJLe+nT58ilUrh97//PfL5PMrl8qlVGFS1VCoViMVifPHFFzg8PMSNGzd4vEIkE6p06AftNLTZbK/cEkNdplwuh1wux1Us8QoCgQAsFguCwSBUKhVzDWhW2G634XQ6uW35OqDvmL7nTqfDYyE6B2/evAmpVIp4PI5ms8lngfA5IkYufX6bzcYuSNSFEYvFXEjQKCKZTOLevXt4/vz5W9nkfR8uLAhS64Cy7EKhALlczizIQCAAAOzxKBKJ2GiWBK40dCUa/GmSRIjoQq4oUqkUmUwGarUaLpcLOp0O5XIZTqeTNU5C6jbNY4TSB/pBLTRKBKi/3263+aCijdaFQgHlchkbGxuIx+NYX19nr86LFM7S/et0Ohy4J4kQcxyUdND33O/3IRaLkc/neROD0WhEq9WC2WxGo9GAxWKBTqfjGRJZP5GMJx6PI5fLnWsQJCOFdrvNBx8dHscrwU6ng1QqdYRoAYDHDMIkTNhtOa9tElR5WiwW1u9ptVqu1Ek28H1eqDRGoESUROoLCwtceWUyGRSLRUQiEcRiMUSjUW4lnhboGSN/40gkgk6nA7PZzDtDqWI7TuCjztL3rbKiIEgkIp1OdyQI+v1+WK1WBINBZgMDL+45BTGlUvlGzk7ERaBzqd1u86Yf+v6dTif7B7daLdZ2CzE7Owuv18uyL5pbC5MukidRp69cLiOfzyMajSKXy52JqcWFb5GgoT2JYGl32J/+6Z/iN7/5DW9PFovF+Oijj+B2u3H9+nU+gNfW1rC+vo7Hjx8jk8mcyeobOjAKhQLEYjFyuRzEYjEePXrErDpyhydGlM1mg8FgwNWrV6FUKjlLVavVvA9re3ubNyYT67DZbPIiXmr7UruEsvvzZCb+UGC1WvEnf/InmJ+fx8rKClKpFAqFAv7xH/8R4XAYX3/9NRMLSIv6k5/8hPc8Wq1WWK1WWCwW3Lp1C0qlEiaTCcVikRclnydomwIFreOgwHZSlUPPUaPRYDbzRdgO6vV6uFwuLC4uYn5+ntuwRN+n94Ke9eOuNtT2XFlZgc/nw9LSEqxWK4u5VSoVEokEnj17hvv372Nvb4/9hxuNxqm/Q9QaLxaLKJfLyGaz0Gg0WFtbw8rKCsbjMe8KpYP/TccHtIhXo9HA5/Phxo0b/Dno+aXkQOjqMhwOeVEwLYl+XVBLejQawev1otPpwO/34+bNm/x30SJgSvBPSqSIHUo/f3xt0nA4ZKu1UqmERqOB/f19RCIRfPnllyxVOm1caBCktk2z2WQrHKfTicXFRW6R9Pt9bikSK0ksFjPZ4ayyuuPXKcyWB4MBtxao0qNgRuy8Wq0Gg8HA/W+aJVIQbLVa2NnZ4UqYmFRU5QmZpcLW6WVxN5k0pijNY8h6jAgU1Coj/Vm/3+fZJr2YwoqbMm5Kas5jdvYyvG3gIqIBdR1OIqCdB+gAJYE+jQooKFN7Vi6XA/hWukQEHuoKkTE6EV/osKd28P7+Pg4ODnhJMml4zwo056MKPJFIQKlUYmNjg51VSAesVCrfaIQglCdRC/hVgXQ8frHZnnR56XSaNXyvCxrVFItFKBQKVCoVmM3mI5ppuodvCqERRL1eRzwe5+us1+tsk0dysLPAhVeCZCBbrVah0+nw5MkT/PrXv0YwGMTt27dx584dflEp8P3ud7/D2toab5OmecdZg27YSS8QySOAFw9qJpNhEenxBaZ06DSbzSOegHTgTopN0ptgEi3ThKBqejgcQiaTYWVlhQ8R2tHY6/UglUqxtLSEq1evwm63w2AwHAl2NA+lauUyGre3Wi2IxWIUi0XOuCeB0ERt9VQqhW63C7PZzLNxmkEtLy9z4CMOAZHpMpkMcrkc/tf/+l9IJpPY3NzkgEhttvNu2/d6PUSjUaTTaTx9+pQXIt+4cQM+nw+BQABKpfK1/zxKCkgDqNfrvzf4xGIxJJNJfP7554hEIrh///4bnZd0XlWrVcjlcmSzWd7tKJxFvy3IG/b58+e4d+8e1tbWsLOzg2q1yn/3WeqhLzwIUilPq5QKhQLS6TQ7KNCuQQoytGAxGo1yAHwXgetp4XiFRvOn4XDIZT9lcfRr6bpPIspcpgAIfLdanjR0Oh0kk0kYDAZotVqEQiFe8SKXy/HJJ5+g3+9DKpXC6/UiGAyyzRPJVWiGHY/HeQnvmxAMJgU0F6KVTAqFglun5zkT7Ha7aDQaKJVKLPmgzQHz8/P4xS9+wWcAtfr8fj/0ej18Ph80Gg10Oh16vR5LYEj8TjID4d7Ri5qhk0UdjX6AF1VtOp1GNBp9o/kcjV9IA2iz2aBWq1/5e8LhMEs2qKX4NpVwq9Viu7Nut8tOUU6nk+ePL2vNUyAjsqHQDGA4HDLfYW9vj6VfxPegs/GscOFBEPiun93BwQGePHnCLurU6iTHC2JETdLyU7qZBPr386hQJw2TGAzr9TrW19dZM/fBBx9gZmYGy8vLmJubw/Ly8hHXInIuIu9F4MW9zOfzePr0Kb755ht8+eWXyOfzF/zJ3hxEIrFarWxOQcSH08jsXxfNZhOFQgHxeJz9SskU32Qy4erVq9/RPtJ9UalU3NaNRCJIpVL4u7/7O166S5X6RZLHCHSuUZVLnqHEFH2TKpw0ey6Xi40NjEbjS3/9ePxiK0+5XEYikUChUHirjS/j8Zhniffu3cPu7i5arRZmZ2fx/vvvw2g0MiP0+Ochkksmk0GhUMD29jZLNKhYSKVS2NnZ4XbteS5Mn4ggSKCMKRqN4g9/+ANqtRqTRPr9PssWaIY2KQHwxwZiuJG3qslkgk6n460ENNc8LyH564Da6WRxJ5PJkM/nebOA3+9n+zcCsTDJuT6fzyOXy2F9fR37+/vI5/MTs4vvXUD302g08hJn0mqdJWimfnh4iNFohK2tLTidToRCIdbWAeBniipxqqqIVX54eIhMJsMVII0ZJiEACkHVNv2TRiRvUnWTcUa9Xkc2m0UymfzeSpBsJrPZLBqNxjs54tD8vN/v4/Hjx2xsTkSkk7oINB+tVquo1+tIJpNMzKHioVKpIJPJnIppwZtiooIgzVvS6TQGgwE/+NRWpDKe2oiT9ID/mECWVBqNhgOgRqPhANLpdDhxmZQN2DQTHI1GaDab7EFrt9sxGo2wsLDAJAUiNJD9FYnTqQUfDoeRy+VOVWN23jherVOL1Ol0YjgcfkdHeBagw448XQ8ODjAcDhEIBHheKzTIGI1G3BmKxWLIZrOIx+M4PDxELpdDLBZjre2kng1UFb6tOblYLOYEQKlUIpVKcbLwMhDR6FVyk9cBXTsVI1TZxuPxI8zP40GQeA5ExDreDh2PXyzYJd3zeZ8ZExUEgRdfWLVaPaIHoWriPPrDU7wehCw1odNNv9/nlhRZvU0KiHnY7/cRjUZRLBYBAHa7nZ2LSKzb7/eRyWRQrVYRjUZRr9eRz+fZrYP+nEk9bF8FIsLkcjmYTCbUajW2iyO283nMBCmwpdNpNBoN/MM//ANsNhu2t7e/U5XX63V0u10Ui0U0m03WZ5KOVij1uIz35HUh5BqQHvH72qkUvE5LWkV/TrFYRKVSeaVUh0DnNl3/cZev07y+N8XEBUHgW6H6FJMNIRlG+DDTkteL0p+9CsJsllrvtVqNWXfE3u33++xYlMlkmBRA+tTL3IongwYhY1LITH6bmdHbgJ4bMsY+PDxEuVxGt9v9DsmCdLKUWBEpjuZUP4S29OviPK36TgLdN/rO30RzOImYyCA4xWSDiEyNRgPFYpHFxwqFgivBeDw+cZWgEGRNRfvQdnZ2jvi2CvVqFBSOm1RfVtAWbxL/057KSqXC2wDeREf2rqA22dbWFiQSCZ48eQLgqNZU2A06/uOy348pLhbTIDjFW4Hmt41GA4VCgbVdxOItl8tvTcU+DwizWeo8CLd8EHnhh3jICvc+CttQrVaLNyCchTPHy0Df93n+nVNMQZgGwSneGBQgaKHw/fv3UavVYDQa0e/3j8hbJv1gE9LXfyyglicRLKjNS2bxjx49Olc/1CmmuEhMg+AUbw1i8IbDYd4nOBwOkUgkUK/XJ4odOsW3IBus58+fI5PJMMuVrPwikci5bZWfYoqLhuhVrR6RSPTD6gNNMcUUU0zxo8N4PH4p3fniDQOnmGKKKaaY4oIwDYJTTDHFFFP8aDENglNMMcUUU/xoMSXGTDHFjwhC7R2J0cmZRejq8UOThUwxxcswDYJTTPEjAC2oJYs7WiqsUChgNBpZN0g2ZGQQMGX3TvFDxzQIvgFe5qd4fKEsHSiUWdOhIzSXfZ0FtMIdg1OHjPOHSqWCXC6HRCJhYT3ZjV0W0B4+2ouoUqk4GGq1WiiVSlgsFnbKoV9HNmX1ep1t1i7Lc0cG7waDgd8dcgi6rH6vU5wdpkHwNXA8gB3/f/TSyWQy9jwcDocYDofsg0hbFsh0WiwWs1cltaWEL6fw5R0MBmi32+h2u2g2mxfuHfhjgc/ng91uh06nw2g0QjweR7VaRTKZvOhLey2IRCJIpVKYzWaEQiF4PB44nU4olUrIZDIOglarlX9PKpVCNpvltTabm5toNBqoVCqX4rmjtVAOhwMfffTRkfVs+Xwe+Xz+UiUxU5w9pkHwFaBDRCaTcUVwPBBKJBLI5XLo9Xro9XpotVrIZDI0m012vdfpdPB4PLysVaFQQCaTwWg0cvA8jsFggMFggHw+j1arxcsmY7EYB8Qfgo/lJIIc8a1WK3w+HxQKBTqdDtLp9BstQL1oUKJltVpx5coVzMzMwOfzQaVSQSaT8XNI2yPG4zHsdjsH+lKpxIuEO50Oer3eRAcQYdD3+Xy4c+cOJ6JisRjj8fjIGp8p3h4SiYQ7C3q9ngsA4NsdgWTK0Gq1UKvVJvasmgbBV0AikXDGrNVquXITQi6XQ61Ww+PxcKatUqnYNmx/fx9OpxPvvfceTCYTDAYDdDod1Go1H0gajQbA0UqQfDi3t7dRKBSwtraGvb09tFotlMvlS9eiukyg+ZnH48HCwgKGwyFqtRp2d3fPZcXQaYACuUqlgsfjwU9/+lMsLy9jdnYWarWaDyzhrwfAhuHRaBS5XA7tdhuRSATZbBYAJrqdSB0Zl8uFpaUl/MVf/AWvHKI2Nu0cnOLdIJVKYbVaYbfbMTMzA61Wyzsox+Mx2u02Wq0W4vE4stksbwqZxGdn4oOgSCSC0WiESqWCzWaDQqFge67hcMgrVWjL92l9yVKpFAaDAX6/H1evXsW1a9egVqu5aqNDg148rVbLwU0mk/F6l2q1CrVaDYfDwVWgXC7nDJy2sZ/09wOA3+9nt//5+Xn4/X5sb2/j4OCA7ck6nc5EPlyXFTqdjqsJv9+PRCLBgfCyrI2htrtSqYTNZsPy8jI/g5TIvay9L5PJYLfboVKp8P7778NkMmFnZwelUgntdnti59IymQw6nQ43b97EysoKNBoNRqMRFAoFtFot1Gr1kR2FU7wZKLEym80wmUy4fv06AoEAbty4AaPRCJ1OB+CFH2+j0UCtVsPW1hYODg6OrOui0RIl8rQI+TTP7zfBxAdBADAYDDAajVhYWOBt5pTZUa+/Wq2emlclLRbVarXwer14//338Wd/9mfQ6XRQKBRHfh3hOPlFuHZHuKhU+IN+/XGMx2M+jGw2G8bjMdxuNzweD6xWK5RKJQBc+MPzQ4VarYbdbofD4YDNZkM6nWZvzUldDXUc9MxRq97r9UKj0fD2b+Bo50GY1IlEIhgMBqjVaiwvL0MkEsFkMqHT6XBbcdKeN2qFqtVqzM/PIxgMQqlUYjweQyaTQalUQi6XX5pKHng5EU+I87wP9EyZzWa4XC4sLy9jfn4eH3zwAcxmMwwGA19TrVZDuVyGQqGAVCpFLBbjIEiJyGAw4K0zRMQ6788EXIIgKJFIMDMzg2AwiD//8z/nG9BqtdBsNvHw4UOEw2FkMhlednpaf69cLodOp4PJZILdbodMJjuSSQoPEyHrk37u+K87/t/f95ALyTiUgVHlaLVaMRqNcHBwgK2trR/VUtGzAr3kPp8Pd+/ehcfjgUqlQq1WQ7FYRK1WuzTG0iRvoG5EMpmE1WrlOfTxtVH0vNLP04wnEAhgOBxicXERUqkU5XJ54pbYUtVrMBjgdDpx8+ZN+Hw+aDQaFAoFJJNJZDIZFIvFid0WIiTYSSQSSCQSTloogZZKpZBKpVAoFExSyuVyaDQaaLVaZ05aosLgs88+w+zsLH72s5/BZDLB4XB8h9dAXa6bN29yJwt48bxRMkKLqp89e4Z0Os1G/N1u91xbpxMfBIEXlaDNZkMoFILVaoXT6eRyO5FIoFqtnlmWRy+YRCJhavmrIAyIwm3rNL8THji0r07YXqLARyxTtVrNPyeXy3kZaqvVgtFohFarPVOyxnFZB+H7/k6hRGTSqoaXgb53o9EIr9cLtVrNe/aazeZE70c8CaPRCP1+H7VaDbFYjDslSqUSEomEM/Ner8dBkw5ak8kEhULBC3idTifK5TJUKhV6vd5EBUF6RhUKBVQqFSwWC4xGI6RSKXq9Hi9+prnURV7ny/5J/ANi7spkMphMJv5vIjnJ5XJotVqe3ZKes9PpnHkQpCDt9XoRDAb5HaFZoPBzSqVSiEQiWCwWfg4JCoUCIpEIzWYTpVIJtVoNYrEYlUrlyFLraRD8N9BM0GazwWq1QqvVslSgXC6fGUuy3++j3W6jWCwik8kgkUjA6XRy3/t1QItCa7Ua0uk0M6VoH9/BwQGazSYqlQpfP70AXq8XFosFP//5z/nvJGkFtXYoUJ5W8Be+lMelH/QiUkKgUqmOyDuEn1nY62+1WqjX66dyfWcJOkSNRiNCoRBu3bqFXC6HSCSCSCSCZDI58fIAIejgKZfL+Oqrr3B4eIiFhQWEQiGeDdbrdTQaDUSjUbRaLVSrVX7P/vN//s+Yn5+HyWSCXq/HZ599Bo1Gw/PRSSKXCFu/SqWS539SqRTZbBb379/HxsYGwuHwhbSz6T0lYh0FCYlEAoVCwf/UaDSw2WzQaDRQq9WYmZmB2Ww+ImnRarVwOp2cmP3f//t/sb6+jidPnpxplUtJuEaj4c4cVaovAyXxXq8XTqfzyJ9Fwa7ZbCIUCiEcDiMYDGJ9fR3hcBjJZPLcui6XIgjSwUttgeFwyCzJdDqNRCKBbrd7aocUVTAUwDKZDCKRCEajEYxG45EAQYe+cBs5aZOoHVWr1ZBMJr8TBPf399FoNFAulzkIkoyCghwNkqnCPKmN9a4JAL2YQjcRITNWpVKx9IMOGqvVylXD8e+u2+2i1Wohk8kgm81yq2aSK0ISldOhr9VqEY/HUS6XUavV0Gg0Jvr6TwI9m41GA+l0GgqFAoPBgGc19Dwmk0muKujQpYMbeLGElyqpSa6GhckbnROdTocJTedRLR0HBTiFQgGdTsfvjEqlgkKhgMFg4HdKp9PB4XBApVIx49xgMPBcjX7eYrGg2WyiVqvBarXCbDafKeGHzl6r1QqXywWz2Qy9Xs/nBXDyaEfIfTgpWNK9sNlsbMzQarXQ7/dRLBanQZBw3FmF9CeZTAbb29v4x3/8Rzx58gStVutUX87RaIR6vY5IJAKxWIxsNovV1VV+SOVyOcxmM1Ow+/0+HzCk6+t2u+h0Omi1WigWi+h0Oly5DodDpNNptNvtIweswWCAwWCAXq9ndht9D8I2KrlfnEb2Ry8m9fHppdRoNPD7/XA4HPB6vdBqtTCZTLBYLLh58ya/lMLgMBwOUS6XkclkcO/ePXz11VfIZrPo9XoTO48BXiQCer0eS0tL8Hg8PE/a399HKpVCsVi8VJUggQwX+v0+Op0OIpEIV/XUDh0MBjCbzfD7/bh58yY++ugjhEIh6PV6SKVSVCoVfP7559jf30c8Hp+oKlAI4VlB1Wq9Xke5XGbd7nkmMlSd2mw2mEwmhEIhfmecTicMBgMWFhag0+mYXe50Oo/Y2wmDi7BTQ63DQCCAdruNr7766sw+B50FH330EZaWljA3N8dM/TeFMHEnkozL5YLFYsHc3Bx8Ph/m5uaQTCZRLpfP4NN8FxMdBOkwpkxKLBZzcMpms9jf30epVDqTQSpVa5RFUyWTTqe/Nwg2m02k0+kjAmPKcISzQWK0drvdI3MBjUbDGhxhpUUvAbW6qOp8189N2sUrV67w/Ecul0OhUMBisUCv13OFoFQqoVKpjmTa9PdTNqpUKmEwGBAIBBCPx+F0OlEsFlGv1ycykNB3r9frsbCwAL1ej2q1ilKphEKhcCEH6GlC2NmgoCjsLlAL0el0wul0crtUJBKhXq+jUqmgUCigVqudasfltEBkEbfbDa/Xyx0a0qoR2eK8dLX0PLlcLphMJly7dg1WqxWhUIjfIWLfOp1OKBQK/nmSsLyqwgK+1bLS2XiWrFepVAqlUgm73Q63280z5ZddHz1vxKhuNBoolUo8kyYuRL/fh0wm47NFrVYzGZFa2u12+8zv2UQHQdL3aDQa9jwcDAYolUo4PDzE06dPWR94FqAWUavVQiqVQi6Xg16v51bG8SBIMxj69W9S/VDmp1KpOCsPBoNH2ghnUQmKRCLYbDZ4PB78+te/5mqAWs/0QtJLSQP5RqPByQf9OcQopJd8YWEB2WwWwWCQZ4STSK8HXnz/FosF7733HmQyGfL5PNLpNFKpFBqNxqWRRrwMNJ8+7pYil8thNBrZWi0QCMDn83EgKRaLyOVyyGazRxLOSQJ5o87NzWFpaYmlEfV6HbVaDbVajRPS8wjgNP8jqcZf/uVfwuFwIBgMMrnleOsW+Lade5xYd9L7IgyCNJ8/CwhngV6vl6vZk8YgQpDVI/EpNjY20Gg00G63+VzsdDrQarVYXV2F2+3G3NwcZDIZ9Ho9jEYjDAbDuTxvEx0EqQ3n9/tht9t5RheNRhGLxXjOdtagLDqXy6FSqXCPXKFQcMVIlSK1nt50dkI33+l0YmZmBqFQiA8j4Oiam0ajgUKhwD30d32xhX17eqmoysvn8yiXy2yd1W630W63kU6nvxOE1Wo1FAoFHA4HvyTPnz9HNBpFtVqdyLkgfW6TyQSbzQa/349sNotYLMbf8SS3cd8WIpEIWq2WW8Dz8/NYWVmBzWZjVmW73cbz58+xs7ODSqUycbNdYmxT12R1dZWDYKPRwO7uLmKxGIv8z/K6KYFVq9XcUv/oo4/gcrmwsLDAybyQ23Dcj/gkKdV4PEaj0UCv10Oj0eAklIgxqVQKhULhzJ5RYbCm7tBJAZdIVplMBvV6naUbmUwG+Xweh4eHbGIurATJl7fZbEKv10OpVCIUCuGTTz6B2+3Gv/zLv/A8+qzu38QGQaLXejwe2O12Fsg3m03kcjnk83kUCoVzoWpT8KlWq2f2d9BMzmKxwO12s1CbNhgALwIh+fHRg3EabjH0oNNsUC6XczDP5XKIxWLY29vjv5NmpcLKgg5VtVrN2aJOp2PLrUlsowHfWuPp9XqYTCZYrVZks1lks1lUq9Vz0V9dBMRiMc94/X4/AoEA/H4/DAYDJBIJms0mGo0GwuEwDg8PufKfpO+CEhi9Xg+bzYZgMIhAIMDPbzweZ/vCXq93ZocovT9KpRJGoxFXrlzB8vIyPvzwQ9bI0Xt1PPAB3634hN8xjX9arRabf1Mi2m63kc/nUalUzqRaOl6h0vkgvH665maziUKhgN3dXeTzeUQiER5bVSoVZDIZHt/QCGc4HDL3QaVSYXZ2lok3q6ur0Gg0ePr0KQd94d93mpjIIEhZ+XvvvYfV1VXMz8/DaDRy67FSqaBWq6HZbF76LJ3aDUajET6fD6FQCLOzs9DpdN9hfLXbbRQKBYTDYayvryORSKBQKJzJC0Atz3g8js3NTTx48ACFQoEDn9C/lD4HGTJns1nWPOXzebbamkSoVCqYTCZ8+OGHWFlZgVgsRrFYxObmJlKp1JkdMBcJSlZWV1fh8Xjw8ccfw+fzYXZ2ls3ft7e3kUgkcO/ePSQSiYk0niZbOEocybtXKpWi0Wjg8ePH2NvbO/NkmUYBRqMRHo8H7733Hm7fvs1mC3K5HMC3BgZESKJqiBi89HPUxqUu09bWFiqVChKJBHMIqCKkWftZMCkp4BAZkYh+wneZpGT7+/vY3t7G119/jXQ6zZwISkCIFX9SwC+VSqhUKmg2m8y1mJub45FTo9FgItdZYCKDIOm17HY7s6jUajWq1Spb7VArblIP19cFtVH0ej3sdjvrtI63HajVWi6XUSwWUSwWzzQ7pxeUhtrZbBb5fP6IBpBatIRerweJRIJ+v8+Zb6PRmNggQocX0dHNZjNTtYvFIksCLtszJrTpO55IiUQi3nhCgcPj8cBms0Gr1XKlkclkEI/HkUqluAKZtISTqhOS8KjVaib0DAYDDg5EACJi3WlDqFOkbo7D4WDCCs21aI5PgU/4c7VajX+uUqmgXC7zO0i+rSRloWeS2ogUFM8C9I7TeIRcuYRBrNvtcrWXSCSQTCZRLBbR6/X417/s+iippu+E2q4ajYZlWWft9zqRQVCn08Hn87GBMVk9lUolziomrTXzNiAboqWlJSwsLOCzzz7DlStXsLCwwP6ghOFwiGw2i3v37mFjYwOxWAyNRuOIE8NpgTJQMgugg7BYLPL/P6ktQeuf6JpIEDuJoENRr9fD4XDgzp07kMvlePr0Kba3txGPx5kNOSkzsNcBmbNbrVao1WrYbLbvzHDcbjdMJhM++ugjOBwOXLlyhYXclPD87ne/w9bWFnZ3d9mjdtK+B6oEydZQyJIkaQIF71KphHq9zjPe0/ws9CzRRhmSOcViMdRqNaRSKTb3aDabHLiEDG/hnlBqRVPwSSQSbDF2fKcj/ftZJprdbpdb40qlEsvLy6wl7ff7qNfrSKfTODg4wP7+Pnvtvg4JTmgHR8GOxj60Seesn72JC4LUVjMYDNBoNEfouKS5o0HxZQZl5GazGTMzM5iZmYHf74fFYvkO22swGKBWq7GDCQ2dzyIAEihLpRkg2TO9DiY18AlxfBZoNBrR7XaRSCRQLBbRarUu5aoqmUwGlUrF9PyFhYUjc2WRSAS73Q69Xg+fzweTycRaz06nwxUHLdelNUST+D0QE5nuoXBeRUbadIYQ0Yn0kmfx7gjJLuPxGIVCAfl8HgcHB0xmI0ILHe4U1KhdKxaLmUBCVRgJ/YWmHMC3Rvv072fFvKazoFAoIJPJHHkmhHIIYaX7OtdBM13hnlWq4kneQqzeH00QFHo3+v1+mM1m9s6k/nc2m0U8HkelUrnoy30nSKVStrH6q7/6K/j9fly5cuU75T+9BLu7u3j8+DH++Z//Gdls9kzF25SJNRoN5PN5JBKJSy8ROA4SAIdCIczNzcHlciEcDuPevXsIh8M8y7hs0Gq1MJvN+OijjzA3N4f/8B/+A2Qy2RHTBXIgEVZOZO23traGp0+f4vnz54jH42eaaL0rlEolSzuWl5ehVqv5/7ndbvyP//E/kMlkEIvFcO/ePWxvb6Pf77Nf5VkdrBTUnj9/jnA4jMePH6NarbJhBgVh4fsrbKcSCxP4th0pEonYo5OC7Hg8ZjN0Yo6eRVuUgtDGxgaq1Sr+/b//95xcEFuYgvnrsodJn6rRaHgMZDKZIJFImPuQyWS4gj9LadXEBEGajdlsNni9Xni9XhiNRiiVSrTbbTSbTSSTSSSTSWSzWTQajYu+5LcGGfzSPi6fz8c2ZMeZVzTb2N7eRjQaRb1eP5cWHf3d3W53ooktbwvyanQ4HLBarbxtIZ1Os4nBZf3MNOukQ/W4ZRVZolGFKGxp7e/v4/nz56hWqxM9y6VWKHVTrFbrd2wMyQDB4/FgdnYW4/EYmUyGD9rTarMdN8CmdVNUzVAQIWG70Wj8jjE9Sa70ej2bUtM4gRyXhM8jBQVinFYqFW5bUiAio3N6lt/2s9JZUKvVUCqVUK1W0Wg0YDKZOEAL9cRCd6uXQSwW8waKQCAAt9sNs9kMsVjMTFjqRPwo2qFUAep0OszOzmJubo6tedRqNevU9vf3cXBwgFgsdmlW2pwEj8cDn8+Hjz/+GH6/H3Nzc9z2FT5ApE+sVCp4+PAhyxROOwgK2zhCVxoStJ62Jd0kgAT9Pp+PV3MVi8VzTTTOAnQPiZgkZCeeBKpayuUyIpEInj59inv37k30Z6cgr9FoYDabYbfb4XK5OAgKCXN6vR4GgwGdTgc6nQ7JZBISiQTpdJqJKKdxPVRZ0+Le8XjMrU8ifOh0OiZ8CO8L/X5iKpOFGvDi/sTj8e8YU1DVRUE3l8uh2Wwik8nw/6tUKhyw3qWlKPzzJBIJisUiLBYLnE4nRqPREb/h1wmC9HkdDgf8fj+Wl5cRCoXgdDqZGZtIJBCLxZicdpa48CAo1Nj4fD785V/+Jebm5hAMBmEwGCCVShGNRnF4eIi1tTUkEolLJY0QMsdIM3T37l2EQiEsLi7CarVCpVJ9hwFFA/R79+4hEong+fPnyOVyp7ozkUD2dGTaTbINChKLi4tIJpOs1aHgLKR6T/KheRLIGIDaTru7u4jH45xd63S678xb6DNPcouw3W6jWq0iHA5DIpEgkUjAaDR+p/ogUNCge6lWq2E2m1Gr1Sb2cyqVSng8HszPz+PGjRtsPUYsyydPniCbzWJ9fR1Go5GrfaPRiA8//BDBYBDdbhe5XA7hcPidr4d2/1mtVvj9fuh0OshkMszNzUGr1cLtdnMb2mw28wJaIfmNggjJjOg9HI/HHEiP+whTtUv2do1Gg7e4DwYDhMNhRCIRRKNRliC8y9lBz0omk4HBYEAoFAIA1gSbTCYYDAZ2hhGSeIRuOPR+3blzBzMzM7hy5QpMJhNkMhkHwCdPnmBrawu9Xu+1Kst3wYUHQeBbrZzVasXt27dZKC6VSjEcDpHL5ZBIJHB4eHimNmlnARr+qtVqLv1XV1cxMzMDj8cDrVZ7JCOkm93pdFCtVvHkyROufokMc9ptOgqC9PIB4EybsrVOp8NtNfJUFTJBL1MgFFZKJEVJJpMoFAr8LNLcjGj1xOAT+r9OIog9nclkoNVqkcvlALyYFQLfXdRMn43aWrSvjrxuJxEymQw2mw1utxszMzMwGo2QSCS8Dmrj/7f3nc+N5dl1ByACkXMGSAAEmMlO0z09eWdng6SVJZdDuVz2N1fZ5fI3/1UuqyStVQq12tHOalLnZje7m5lEzjkDJAj4w9S988gO04EE0DM4VV0rzUyTD3jv/W4695wnT7C3t4fPP/8cDocDMzMz+PDDD2E2mxEIBGA0GrGxsYFer4dQKPTG95Ksxcj3lGTFnE4n64NKJBKo1WpWtzEajSd8+N70GqgVajab+RmlmV21WuV1hdNrTa8CCoL5fJ5HCEKPQ51OB4PBgEajwQSXw8NDrhSJAapSqaDX6zE7Owu/3w+3282WUq1WC8ViEdFoFNFolEW2KXj/KJflT/fDXS4XtFotZDIZv6DUDqXF0LcF5KflcDiwvLyMpaUlzM/PY2Fh4YTLN/C9OgPt1FDgv3HjBiKRCHK5HGfsZwmRSAS3241gMAiXywWTyQSxWAydTodAIACFQoF3330X9+7d4xWJarWKra0tlMtl3qcjhwxhxjqKoJfRYDDA4XDA5/NBqVTizp07aLfbWFlZ4ZdZqVRCKpXyQvDu7i635Udxbw4Az47C4TDa7TZ+97vfweVyYW5uDplMBvl8ntmhwWCQ50+UydMsahRB1ZTBYMDMzAzm5uawsLAAmUyGfD6Pzz//HKFQCH/4wx+Qy+VY97VYLHJwIhYpyZedBSjA2Ww2BAIBtkdaWVnhd1bYpqYqT+iFSu/Nyx7yVFlRJdjtdiGTyTA3Nwfgu+fcaDRienoaarUaBwcHePjwIavPvA6In/DXf/3XmJubg9/vh81mg8vlwrVr17CwsICf/exnKJVK2NjYQD6fx8bGBt8zUv/yer3sqkGmzfTM0crS4uIii23QqIJmnGd9vgw9CNKNVCgUrL1HO0vkS0f7PUSXHWUIsx7SpLRarfD5fPzHYrFwoKchulB7tN1unxAuLhQK5zqjIg1GoVA2vdgulwt6vZ5doAGwaEGxWIRKpUKpVEK9Xufh/FlIuZ0XhE4dNC+i567X63FGbzQauRokyjZlvsQurFarA7lmaiO9zCFJs9xarQaZTIZQKIROpwOpVIp4PM7+jmazGU6nk+8zEWnoUB1VUBub7MZ0Oh13JkKhELa3t3k/j3gDpEpSqVSgVqu5jXhWotNCYgxVNBMTE9DpdCeYk5TgkgyY0Hf0h5bKhb8L+N7+jJ5ROhepMlMoFDCZTDg+PsbU1BSOjo4QiUTQ6/VeW0eVlvfj8TiUSiUKhQJUKhUAQK/Xw2AwQKPRoF6vY2Jiggk9pOozPT3NlblOp4NarebvipIB8lX0eDzo9/tQqVSo1+uQyWSo1WrsRnGWCejQgyAdSOQlRVmaSCRCLBZDNBrFxsYG9vb2mLAwiqBgTocq6TDOzs7C4/Hg8uXLcLlcPMA/7cpOO3nJZBLpdBo3btxAKBRiQdrzCir9fh97e3vodrtYXFzE8fExbDYbH7ykxPHhhx9yFXp8fIy/+Iu/QKPRQLlcxu7uLmKxGL755hskEglsb2+PbLIidOmYmZmBx+OBxWLB//pf/wvNZhPFYpHnsbQvqNPpIJVKceHCBZRKJWxtbeHGjRv46quvzrU1SpUDVWuVSuUHEwyqKuhd+frrr6FWq3Hjxg3UajU0Gg2eSdNaAT27QiPdUQR1VnQ6HaxWK/R6PeRyOTKZDFKpFG7evInt7W2k02lWICHXgkQiwZY9RM8/LUjxuqAgRqopLpeL/x3tX9K/J9YjsZDp/Q6FQrwQ/yJQwKWFfI/HA7VajUKhAJFIxKYD77zzDoxGI2ZmZiCRSLC6ugqRSIRQKIR//dd/fe0gQrPxcrmM+/fvo9VqwWKxsB0bMd+1Wi06nQ4++OCDE0ICtBZBZ6DwcwHgAkGv1/OeIAn2r62t4fe//z3rkZ4Va3RoQZAyFpKrWlhYwNTUFPd/SbopGo2ye8NZewaeBU4vfNJNnJ2dhclkwsLCwgn5N9rNErIwSSE+l8tx4Kc54CBYivV6nZmRJGpLpBFKSqgKoQdaoVBApVJBpVLx/CEWi6HX63HGOYrtQlqwViqVXP3RekSlUkE8Hke9Xmc6eKvVglKp5J1CsVgMm812Yn3nrIyNaV5C36/QrUQmk3EV8TLvAVUZpHrTarX479EzS9WQUBqLfseovWeE0ztpVKXXajVUKhUm9FDL7HSHpdfrsaAAvYtv+ll7vR7P8NPpNAqFAtRqNScixWKRW3q0QJ/L5VCtVpHP51Gv1xGPx9FqtX6wu0BBsFqtsp6rUqlkk11igyoUCvh8PkxMTLAbvclkQrFYPJNE5/j4mIOUMBGkZ4r2CGnmTucGdchO+yWStB21io1GIzQaDTPU5XI5arUaotEon7XUeXrTwmhoQZAcyv/0T/8UPp8P77//Pmdq5AZ9//593L9/HxsbGygUCiN3qFJGaTQaYTKZePBOMlw2mw0rKytMNnlWm4naiqlUCpubm1hfX8fGxgbW1taQzWYHsg9IAsOff/45TCYTtre3YTQaYbfb2VQX+C7gk9USaU1qNBrodDoEg0F0Oh1YLBbs7Oyg3++P5PxWOMQn89xSqYTPP/8csVgMDx48OLHfdXx8DIlEAp1Oh1/84hfsVkDkrUwmcybPJVHnFxYW2GVbOO85OjrC7373O86Mf2g2TPR/amGLRCJmJ5O2JXljEuGh3W6jXq+PrH0UBRvhiIR0XrPZLAqFwlOC59Rmo79HTHSLxcIz7jfF4eEhisUi9vb2WAqx0Wjg0aNHyOVy2NnZQaVS4VY0PVt0X+m7f9nEUSQScVBNJpOs1wuAmZdra2v48MMP8f777yMYDMJms8Hj8aBWq51Ju5uCIO3xUdJBwY3apHR2nL7+50HY5gW+72yQk5DD4cD6+jr29vbw8OFD5HI5ZLPZN+JKDCUI0oNIw2SHwwGTyQS1Wg2RSIRqtYpQKIR4PI50Oj1yzt7UPqI9Jb/fz1qnfr8fJpMJPp8PGo2GW0zCa6cDihhdu7u7iEajWFtbw87ODkKhEOr1+sA+b7vdhkgkQiKR4JYbLSHT8q5wlUWtVmN6eppFzimzNplMrP5Ayvijcs8IUqkUarWaZze0i/T48WOk02k2Q6ZDqt/vQ6FQYHJy8sRKCDHfzmpIT9/dhQsXYLVaEQwGeVZCB/idO3eQTCaZHPCs71Zozky7ZzSrcjgcsNlsmJmZgcvl4rYUVYo0RxtlXV6i/wuFl+nPaV3NQYGCc6FQQCgUwt27dxGPx3FwcMDuD81mE6VSickdQjshIUP3ZSAUBKA9PQoCtCMpEomQyWSQzWZPsC9PC3K8LqRSKbc+qWvxOj9XKAEHnKwMCZR8GwwGTE9P4/DwECqVCpVKBRKJhHenXzcQDjwIUgCh3r7L5YLb7YbJZGL1g2KxiM3NTQ6EozYLpBaVyWTied/i4iIWFhbg8XhOkF6Ap2+00IW+UChgfX0du7u7+Oabb5BKpZjWPiiQjNPh4SETKKjio9UJCoIKhQJ6vR4LCwsIBAJ8aJOnW6vVgtPpRLfbRTweH+jneBkQC5mCxO7uLjKZDG7fvn1CvV+4mAx8Lx1FAZA0KM/q0LXb7ZiZmcF7770Ht9uNQCDAyRO1an//+9+zpJvwGoWgdpPJZOKdP5JS83g8cLlcWFpagtVqhU6nA/Ad25eITURAG0VQxUqBhDQ2hc4MP5R0CTU2zypBo6qI5nvlchkqlYrb6dSipeflLH6vMBk7jU6nc0Jhi0x9KQieBaRSKZxOJwuaCM2/X4RnBUrh/Th9ZtLfkclkMJlM0Gg0UKvV8Hg8yGazEIvFPMYZ+SAoPERVKhVcLhe8Xi8cDgfMZjMAoFwuIxqN4t69e7h79y4ikQhKpdJQZxRCJRWa0RiNRlgsFvzyl7+Ex+PBysoKWyBRdn1a/kyYucXjcRSLRdy9exfpdBp3797leeDr0pffBMIKRywWo91un9jrEfbvSRWDCCQmk4kDptASqlqtnvuS66uA5mAajQZmsxkajQZyuRyJRILFlYmxd/oFtNvtsNlsUKvVOD4+RjgcRjabPbN5IAAYjUa4XC5MTU3Bbrdz9U3XIpVK4fP5UCwWoVarn5rF0LUSkSkYDEKn08HpdJ5YGKdnV6FQ8Ow9HA5jb28POzs7KJVKZ/J5zgun1Y1etvqguRQFonw+f2Ym2fR+0z05PDxkVjElKzTzGsQ7cXrl4ix/H5kxm81meDwe2Gw2KJVKSCSSE8HsWS4SFKiE1R4lEEJ5Rgru9J0JeRc0a3Q4HLDb7SiVSpDL5byi9ToYaCUo1Pszm81MMCDaMtl1HBwcYH9/n4fGw5TsomEtUaBpUdfj8eDdd9/lHSyh+giBHgAiHNDOUCaTQSKRwL1795BIJPDo0SOecwwD9LBSVfOih4laa61WCwaDAcViEQ6Hg/eUlEoltFott7ZHBSS1RYGaKkGyDiKnjNOYmJiAXq/nlYlut4tCocAtmLOoBEUiES8Qk+qGMJGiBMzhcMDj8XD77VkMXL1eD41Gg/n5eWbB0o4WZdG0H0fG1KlUCslkEolEYqQ1eU8/Ty/7fAnVSqhtSvtyZxUg+v0+V6StVourF+p8vcr1nsW1CNuLZ/V76XtUKpXMBNVqtUx0oaBGpKzT7enTqw30nZXLZTSbTa6YTwtSUOdNr9fDbrdzzNBqtazO8yZkn4EFQdoFtNvtCAQCuHr1Kubm5mC326FSqdBqtRCPx/EP//AP7EtVr9fPtOX0qqDKwW63w263w+v1wmKx4PLlyzCbzQgGg1wBPWvxllhpxWIR4XAYqVQK6XQat2/fRiKRQDgcRqPRYEPNtwEUyFOpFHK5HMrlMu84EVPU4XCcGengrCCRSHjOabPZ+OUhVuGzDkMKKLOzs7BYLOj3+ygWi7h//z7i8fiZsZX7/T6y2SzC4TDC4TCOjo6Y2SeU0/rkk0+wtLSEeDx+wm6HIBKJ2IB6bm6O2bvUIqX5NLUTyT2e2qwPHjwYSifiZUH0fKoahNXw8w56qgBJEIASVWqjngfonrlcLkilUpRKJRayHgSIHGO1WuFyuXhtC3gzmzNKxqxWK6xWK8+bSdqt0+nwWlGhUDgR9IjMI9R8pvOxUCigWq2iUCjwTJqSFfqd9Ey/9957AMDdQ0pu3iTQDywI0nCT2mV2ux0Oh4P3dsidOBKJcGY+LFdvYn0ScYfMfQOBAKxWK5aWlliP8XSf/fTcr1gsIp1OY29vj12Xd3Z2kEqlUCwWuUIclbbhD4GyTJrJUFCkBWShDukoVYJE0Z6cnOQqUCwWP9P/jCp/Uo6hJWDhKstZk35I2SSXy0GhUMDlcp34DicmJrglq1Qqn3uokjgzkSHo2RTOpYkFmkwmEYvFEAqFkEwmR74VCpx0On8ZIoxQ3JpEq4UrFucBOripe9BsNgd2jtFzTkICpF5DLOM3PWvo55OwAgBewCcDYVoVOa2q1Gg0TizqU1JDdkmlUomDoDC5kUgkTEIkxvbp2e6bfKaBBUGZTAar1Qq/349Lly5hZWUFMzMzrMkYiUSwt7eHJ0+esAzXsAKDUqnEpUuXEAwG8Ytf/IIZj8QqpHbVs5hW1A+PxWLs0B2JRHDv3j3OXmm/ZZT3sV4GwnYd8H3WfVoIYBRA2aRKpWKlf5o9CLNVqVTKc7PFxUU4HA643W70+9/5qZGY+1mvEITDYZTLZdjtduRyOTgcDmg0GhbyFovF0Ov10Ol0sNvtAJ6d1VNm/Cy2HrWqKCH7u7/7O0SjUdy/f39kxQ2ehdO7gi96h2j84nA4MD09DZvNhk6nc67PJ1Xu7777LndHSF5QOHY4j99LMo2rq6tYWlrCzMwM7w+SbN6bnDnClieddc1mk8dY3377LRKJBA4ODrhSp+eQzr/TllBCT0IKaFTdUcDVaDRYWFhggQQATOZ7047MQIIgfRiarQjd02kxORqNIpVKPXPgP2hQFSDUudPr9bzsSb1+4SFD2SnNGg4ODpBMJrG3t8ceiNQeEGY6byOEGoiUCIhEIs4GaWY2ip/vdNYo1HSkJV/SFPX5fDCbzTyvzmazTNQ664Os1WpBLBYjHA6j1+vhyZMnTD6gfcxX0boUtgjp2axUKqjVatjb20MkEuFE7TycSc4TJHBA+5z9fv+E5Bt9dprnejweZjJKJBLebTuvXUh6nojz4HA4mPUO4Mx/L31WmUzG+70+nw9Wq5WX9qvVKrLZLIrF4hsHQeFKCs3/yuUyUqkU4vE4YrEYstnsU528V0n8ac5HSavNZuM1un7/e5sqMhUY+T1B0iecmZmB3++Hz+fD5OQkDg8PkclkkE6n8cUXX2B/f58j+zAxMTHB5JfFxUW2NxHidJZNLyXJNn3xxRdIJpNYW1tjzbsfC2g4TjJIROIgws+DBw8QDodHKggKX17hvIGSGpImc7lceOedd/Dee+/BYrFALpfjiy++QCQSwfr6OqrV6rlk8tQq+vrrr6HT6RCJRBAMBvHJJ59gbm6O/eVeFsLnk1RVdnZ2sL29jd///vcIhULY3d09U4broEACE7lcDqlUCv1+n9eSJBIJjo6OeA44OzuLTz/9FNevX4ff72cvUrL7OQ9QR2Fubg4ul4uT4lKphGKxeEI4+01BXQKVSgWNRoOlpSXMzc3h5z//OQvib25uYm9vD2tra+yj+Lqg+R85qtBniUajePToER49eoRkMvnaSb5wi0ChUGBmZgYWi4UrW5vNxoYKsViMRdLfZK3n3IMgUWqNRiOcTidv/vf7fVSrVRwcHCAcDmNjYwPpdHpkXAieVTGc/vfAdxl8oVDgP1tbW0in09jd3WUa9ijtOJ4FJicn4Xa74XA4uE1MS6vZbBbRaBSZTGakgiCtA9ALTBYter2eg53ZbMalS5cwNTUFs9nMxJ/NzU0kk8lz3VeldhC9zJFIBEdHR2wAG4lEuBX0vFYetaeE2qHEem2324hEIojH4wiFQshms9yReNvQ7XZRqVSQz+eRSqV45eWdd96Bw+FApVLhhGZubg4rKyuQy+UolUqsc5tKpVAul8/tGSUTWqPRyI4I0WiU7YLetBtEwY/m7+TQ8N5772FqagputxsqlYqfBZq7vQkjllqhJB5PyQYxRe12OwwGA+9Kvs7vIZa93++HxWLBz372M5hMJrhcLvaNJPNgEkUf+XYozTIsFgumpqbgdDphNpt5AXhjYwPb29t48OAB98xHARQEX2RxQl5dQvPKra0tZLNZ7O7usgTVqHyms4JCoYDf72dVeGJalstlJJNJznpH6XOT04BQFmxiYgImkwndbpdbSL/5zW9YV3NtbQ1PnjzB/fv32TniPD9Tv99nwedQKMR2QHSo+f1+GAyGF7ZF6YAlJ4VIJMLL/aStSXqiwyKevSmIcJbJZDg5MBgM+Pjjj5mcodPpcOnSJVgsFjgcDqRSKTbaDYVCiMViaDQa53J9dG7kcjlYLBZcvXoVBoMBoVCIq1ghwedVIRQ8V6vVUKlUCAaDmJ6exi9+8QsOSNSdKpfLnJC/yRlLn6tUKrFuKZ3vdrsdU1NTsNls/I696rNFFaBWq2Uxjv/8n/8zP/NUiNRqNcTjcW7vvmnn8NyDoEwmw8zMDN8ks9nM0Z4sNkh0mnq9wz48u90uUqkUO7qfdn+gWUQoFEIikcDa2hpisRhnmJQJve3El9Og9qHBYMDly5cxNzfHQYTU8fP5/EjOO3u9HprNJjKZDLa3t2GxWKBSqfDrX/+abYqI7LS7u8v6rbFYjKnbg/hMwsVroUB0JpNBNBpl14fnQchKpi4FEUhoofhZO1xvE6gSJMH2TqeDRCLBMzgSSe/1ekin00gkEtjf30cymcTDhw+RzWa5nXde10et7Ww2i0AgAL1ej7/8y7/E7OwsAoEAHj9+jGQyiVQq9UojIGJ+OhwOOJ1OLC4uwm63Y25ujv0D+/0+J1CpVApPnjzBwcEB6vX6mRCgiA0aDodZk9ZsNuPChQsol8twuVy4c+cO6/LSWgtBo9Gwhi+RXtRqNQdTs9mMlZUV2Gw26HQ6iMViVKtVdqh5+PAhdnd3EQqF3o4gSHslpFhBeprkX0a2GURBpz79MA/RbreLUqmETCaDcDgMmUwGg8EA4LtshSyEiGDw5MkTxONxpge/iY7dqEKoHarT6eD3++F0OqHRaJhwUSqVzqQ9cR4gt45yucwu8larFVeuXOEEjBbH4/E47ty5w4INpCQzKND8kkgHxCguFAqQyWQAni8/RZ2LRqPB9lxCMYQfw3NJrW06ACcmJtBoNGAwGHiJemJiAoeHh6hUKjymiMfjiEQiXAmfZyv08PAQOzs76Ha7KJfLsNlsWF1dZQcESqrq9Trv2AEnJcSItCXchSNHiOnpaczOzuL69euYnp5mngWNJfL5PKLRKA4ODk4QoM6q/U18Dp1Oh2azyas7c3NzUCgUnBCf9i8UiUSsR0zSfhaLhcWx3W43bDYb/H4/s/CpixGNRnHnzh1sbm4iEomwatObJnMDCYKkXK/VatnDi3a1lpaWYDabuYX4xz/+8VyZWy+Dw8ND7O/vo1arodVqYWVlBclkkhePSbn8n//5n5HL5RCNRk+o+7+tGfbzIBKJeNn4s88+w+zsLFZXV1khnqyfiBAzynR7ykwbjQa+/PJLmM1myGQynqc1Gg0m+NTr9aGKSVMbnpaMq9XqD1L7hQGPgqLw3/0YQPtldMC2223EYjHU63VotVr+jkgZplQqsR0btfHOu619fHzM6wj/5//8HwSDQXz66afQarX44IMPMDU1hUKhgO3tbRSLRezv73PiQ2baJHnncrlYqoyW4M1mMywWCzNAScWJqr6vvvoKmUyGRbTPqgoktFotbGxsoN/vw263cyBbXV1lQ4F6vY58Ps8C8ASDwcDJtFwu591WrVYLrVbLdmLHx8e4efMmMpkMd2W2traYfX5WrOZzD4J0uAhlw+hQodUJoVjzKIAyaVJ6oYBNGnn5fB75fB4HBwdc8v9Ygx+tQdB6SzAYhM/ng06nY7o5Wbrk83kWoB5V0AFI1SBZ0QDfVRhHR0dPUa+HGTyEgextJLGcF4QkIKrsYrEYy8JRNU1yXJVKhTUqB/F8kqBErVbD/v4+pFIp8vk8LBYLi5mbTCZMTEygWCxy5UrKS3K5nP8br9fLylVqtZqFpKmtKBaLmWNxcHCA3d1dDq7lcplbv2f5HB8dHSGfz7NBMACWpROLxbykLxaLeTZJ/w35larVapYyJGYv3TcqKmjktLW1dSKgUwA8i8907kGw0+nwmoDNZoPP54NCoeBFx52dHUQiEdy4ceOEI/QwQZkm+ZNtbW2dcN2meQq9UKN86L8uaO/IZDLBYDDgypUrcLvd+PWvfw2j0QilUolcLodwOIy7d+8y4eAsevTnCTo4qf10urISVlJjjDboXpFH37O88k4vYQ8yoTk6OkK1WsXa2hqq1SqbbFNSSbO0TqeDixcv8qFOPok6nQ6Tk5O8o0wsbLlczudOOp1GuVzGjRs32H29UCiwITetA5315261Wtjc3EQ+n0c6nWY3eZL6o/eMArvwTKCdTqE7zWlBdFKkIlH3UCiEdrt9pk4chHMPgmTsSdJhdFNogL+7u4tEIoFsNotKpTJShw89aIPS/BsFUHVOVlekFB8MBuF0OmEwGCCRSLhluL+/j0QigVwux0vIo952Ex6Go/S8jfF6oHs5au8pVfHUVYpEIjwTdDgc3LoVkrLo2RR6QZI4NaloVatVrpTIkWZ7exvZbJaJeTT/O6+EtNfroV6vnxDVJiUmEiygal3YzaDFfmK4Pk9akeJDMpnktabz+jyiFx1YIpHojU8z0uHU6XQIBAIwm82w2+3srBCJRFAsFrGxsTHSs6SfCkg2zOFwIBgMsrwdWfOQc8SXX36J/f19rK+vIxqN8sxl1A6iMcYYBWg0Gng8HiaxkNu7zWZjspMQQsUf4HtGJhGCaCQTj8dRKpWws7PD889Bt/DPUyP4rD5Hv99/7kUOZCZ4dHSEer2OWCyGYrGIVCrFVRaJpo7nHaMBWiXIZrOcdW5tbcFsNvPclhQwCoUCUqkUSqXSwBmUY4zxNuHw8BD5fJ737Gh++bJyeELFI5IMazQaqFQqaLVa7FQxjBn2qHd+fgjnXgmOMcYYY4wxxjDxokpwtKT+xxhjjDHGGGOAGAfBMcYYY4wxfrIYB8ExxhhjjDF+shiYqe4YPy4QNZp0GqVSKQsGkHLOmCgzxhhjjDrGQXCMV4bQJNlqteLChQvwer3stHDr1i2Uy2XkcrlhX+oYY4wxxgsxDoKvAPLumpyc5IVQUvoHwAuttAP5Y4VYLOYgOD09jbm5OQSDQaTTaeTzeWxsbKDdbvN3NMZgQQvJJPUnlUohl8vZRYJWksZCAWMMGiKRCHK5nBflxWIxCwWQMIBYLGblMFq9onP2PPaQx0HwFUAisS6XiwVeSR+QAl8mk2Hzyh9rO1AikUCj0cDv9+Pjjz/Gxx9/jKWlJezt7SEWi+Hu3btv5PQ8xuuDDhbymfN6vTAYDHA6nUgkEkilUojFYmy6O05SxhgU6Nkk9wiJRAKZTAaj0Qi1Ws3C2jKZDOVyGc1mE/v7+yySTso7Z/3MjoPgK4CMgZeXl6FSqbjyK5VKnKVEIhG2FCJ9VMpihDJswv8dtKbhm0AqlUKpVMJqtcLj8WB+fh5Go/GE7t95KkicFygjJb8+sVgMuVzOAuLP0qQkjVky7KVnYJh6sjKZDDKZjM2rr1y5AqvVCp/Ph+3tbezv77PN0nm7KYwxhpA7QGIbc3NzMBgM7ClrtVp5tKJUKiGXy5HP51k/lcywScCDjKPP6h0bB8FXgN1uRyAQwHvvvQe9Xg+xWIxms4l8Ps+HisFgQC6XYwsRUnCnFlS320Wz2WS3AmHrdNQPJJoFqlQqOBwOeL1eLC0tQafTndALfNsg9Eo0m80nnDMUCgXkcvlTQtsU6EjRPplMotVqnbinw/g+5HI5VCoVpqam4PF48NFHH8HlcmF+fh5WqxVarRYHBwcol8uo1+sDvbYxfnoQiUSQSqUsBK7X67G8vAyHw8F6oy6XC2azGW63m22VSIlKpVKhUqmgXC7j4OAAtVoNhULhTN+vgQVB+jLIRNdgMEClUnEfWHiIkv8U+fmRB9iw2zd0fRMTE5icnITFYgEA+P1+NixdXFxk+5Z2u41cLscmvM1mE+12G4VCgQ1c6fO1Wq2RP5TEYjH0ej2cTicuXbqE2dlZGI1GNJtNNi+tVCqsHD/KM0ES8KWZmVqtht1ux+XLl1nkeHp6GiaTiW2jhKCEJp1Oo1Qq4e7duygUCkgkEqjVasjn89wJGNTnEYvFsNvtsNls+PDDDzE1NYVLly6xDyZ507ndbrRaLUgkEnQ6HRZbpspwVO/ZTw0SiQQTExOw2+1sl0SyaefhDHGWoOqPHOMpaXa73fjwww/hcDhOWNTJ5XJ+F0UiEceHTz75BO12G7VaDdvb29BoNHjy5AlCoRDK5fKZVIQDC4JEptBqtXA6nXC5XDAYDFAoFCe0846Pj1Gv15ldWK1WuXoiFfFh3Xxqd1EWolarIZPJoFAo+PBwuVx8vVQhkLkk6f3R3FAikaBWq/H3M+pBUCQSQaVSwWAwYHp6GlarFZOTkyzoWy6XUa1WuSU4yiArF41Gg8nJSZhMJkxNTWFpaYkz1NnZWVitVhiNRkil0hN/n3Qc4/E48vk86vU60uk0AHCSQ3qPg3he6dAxGAyw2WwIBAKYnp6Gy+Vinze5XA6NRgOTyYRKpcLEg0qlwrqTw/ZPHOM7ELlJJpPBZrNxEtZsNrkFP8qcAxovaDQamM1meL1ezM3NwefzYWFhATab7USH5fS4QalUstEumV1PTEygWq2iVCqhWCxyTHhrgqBcLofL5cLCwgKuXLmCpaUluFwuzlKpajg+Pka5XOasOp/PY319Hfl8Hnt7e1xlUeU1SGxubiKbzeLw8JAzGrPZDI/Hc2ImRtYik5OTUKlU3B6jFhpdOynBf/vtt3jy5Al+97vfjSxrjyp5cphYXFyE0WhEpVLB559/jhs3bqDRaKDZbCIej7O32yhWg5RpGgwGfPTRR3A6nZifn4fFYsHs7Cxn4OR79qLky+12w+l0wuv1srD4xsYG/vZv/xbxeByJRGIggYUy7uXlZczNzeHSpUswmUxs7lqv1xGJRLCxsYEPP/wQv/rVr1Aul1EsFnH37l0kk0l2Img0GiNfafyYQVW9VquFwWDAf/pP/wkajQb37t1DPB7H+vo6qtUqarXayJ0VNFrQ6/UwmUy4du0alpaW8Omnn8JoNEKn07GZ7stwB8jYW6PRYHFxER6PB1qtFkajETdu3EAmk0GhUHijWDCwIEiUerPZDJvNBovFApPJhMnJyRMeVL1ej1lDExMT0Gq1qNVqUKlU7BBN87dBv6gUfMPhMDqdDiwWCwqFAtrtNiYmJrhNerp1RqCHm3y3VCoVtFotMpkMKpUK9Ho96vU6Wq3WyB1ARLlXqVTQaDTQ6XScmcXjcezt7aHT6eDw8JCJF6MIqpi0Wi1MJhN8Ph88Hs8JqyhhW/7o6IhbLsIXjb4Ps9kMtVoNtVrN7fpqtQqdTodCocB+ced9P2nmYrVaYbPZoNPpoFAocHh4iGq1inQ6zf5vdrsdJpMJzWaTSVxyuRyNRgO5XA4ikYj924YNYXIJPD03H7X35KwgnL+Tw3y1WsXExARisRh3m0atfU0dFpPJBLvdjpmZGczMzMDn83F197IQEu3EYjFUKhWUSiV3EnU6HarVKsRi8egHQYlEAp1Oh+XlZfj9flgsFjSbTUSjUXYKFj7oSqUSarUawWAQcrkcwWAQhUIBLpcL8Xgc9+7dQ7FYRLFY5GA4CNTrdTSbTXz99deQSCT43e9+x+1QjUYDjUaDQCAAo9H4zL8vl8shk8ng8/lgNBoxPz8Pg8GADz/8kG/oo0ePsLW1NXLmtCqVCnq9Hl6vl2dlmUwGOzs7ePToETY2NtDpdLhqGiZD8kWgFsvCwgKCwSA+++wzOJ1O6HQ67kLUajVUKhWEw2HkcjnEYjE0Gg3U63W+JzqdDnq9Hv/xP/5HLC8vA/juADCZTPwnm81CJpMN5LtwOBy4cOECLl++jGAwCKVSiePjYyQSCWxsbOCf/umf8M477+C9997D1NQUW/h0u13Mz88jlUphc3MT9+/fx8bGBh49eoRCoTC0Z5DagVKp9IT5KlXVlFhQcjJK78qbgubV1Lr2+Xzwer1YWFjA48eP0Wg0sLm5yZ2XUUhWCBqNBnq9Hj//+c8RDAbxF3/xF8wDeVPWOCVEXq8XIpEIBwcH6Ha7vDbxut/DuQdBWo5UKpUwGo0Qi8Xsstxut1Gv10+4DotEIv4i/X4/zGYz5HI5TCYT5ubmoFarUavVOBsiAsogQC8eLYJ3Oh1+UWu1GpRKJUQi0XOVUmQyGaRSKbrdLmfsxIaidhYt4o9aG5GukYgiYrEY3W6XXaypOh/lA0kkEkGhUMBoNMLpdMLj8UCj0UAmk3EbMJVKIZ/PI5vNIhqNolgsIp1Os6EptYW73S7kcvmJDJTo21RBDqIClEqlUKlUsFqtcDqdMJlM0Gq16PV66HQ6yOfzSKfTiMfjCAaD3G4n9/KJiQlOAIiA0O/3US6XIZFIkMvlBj52oNmzTqeD2+2GyWRi13XyzaM9x3a7jWq1eqJ7MqrP36tAKHhAnTF6B0mmkAiFowCpVAqpVAqXy3ViJk1n2ml2NQUt8prtdDon3OOJLGOxWJ5KhDQaDa+rdTodpNNpVCoVlEql17r2cw+C1Numi65Wq1hfX8ft27cRCoVQKpVOqADQS2k2m/Hzn/8cS0tLuH79OiwWC9xuN/L5POx2O+7du4der4dQKDTQxWxhxkHXLRaLUavVMDExgWw2+9x2KJX18XicacHEmlKr1TCbzRxIRwk0Q7Pb7fD7/XC5XACATqfDzFZhBTiKoO/eaDRiZmYGFy9exMrKCgeA3d1dpFIprK+vIxQKYW9vjxm91A7t9XqQyWTQ6XQ84xbi6OgIqVQK2WyWk7PzDoQajQYzMzNYWFjAysoKpqamYDab2YF8a2sLW1tb2N7eRiAQ4E6FVCqFTCbjeYtCoYDJZILZbMb8/DxkMhl2d3fxxz/+EY1G49yu/zRoBmSz2bC0tIQ///M/x7Vr16BWq9HtdvHw4UPmBxQKBaTTaezs7CCZTHJrcJQqo9cFfQ80O6MVHloml0gkIxUEKWm5du0agsEgPvnkE1gsFmg0mqcCIPDdOdpoNFCtVrG9vY10Oo2DgwNUq1U0m034fD5YrVb86le/gk6ng1Kp5L9rMpmg0Wjw4Ycfwu12o1QqIR6Po1wuv9a7NpAgKNy1oshPf04zCfv9PprNJgqFAh48eMALkk6nEwsLCxCJRJienka5XEY+n0ehUECxWDzvj/FCCNszrVbrqZtO1aJWq4VWq4XH44HH42F2bLVaRTab5aRgFEkJNEuTy+XMlBR+7rcJlGUTK5ncvqklmEqlkMlkmIlHlRCRZSwWC7xeLxYXF6HT6fjn0s8plUq83nNelTEdkgaDAcFgEF6vF06nEyqVChMTEzzvC4VCvLaxs7MDmUyGeDwOvV4Pn88HjUYDp9PJ0moGgwFisRgrKyvQaDTIZrPIZrNIJBJDaXHTjplGowEAzMzMwGazwWw2o16vo1Kp4MKFCyiVSrxETYzsTCaDdrvNKyBvy7NKs8DZ2VksLCzwZ69Wq6hWq2g0GkNzkT8NWoKnMcny8jK8Xi9MJhPUavVTgbrX66HdbqPVauHhw4fI5XLY3NxEPp9HMpnkpJNWyQKBACff9HOoyDAYDKjX65zEvW73bCDt0MnJScjlcgDA4eEht56IRi6EsKVUrVbx+PFjiMVifvi1Wi28Xi8ajQYqlQo2NzeH3joUDqef1TqiNqhGo+HKj+ZqcrmcD+C9vT0Ui8WRpD5Ta4baHgDeqnmM8B5Ru1ksFvMaQ6lUQjKZxMbGBsrlMkql0onPJmT80sB/dXWVgyBVIDSrpkrwvNi+RJwwGo1MPXe73RwEG40GCoUC9vf3ma27tbWFQqEAi8UCnU6Hy5cvw263QyqVQq/XQ61Ww2g0QqPRoN1uw2azIR6P82x0UPN34X2iVqBSqYRMJoNcLke320UgEOBdTQoKxWIRtVoNa2trSKVSePDgATNgO53OwFrUbwpqcS8sLOCdd97hIFipVFCpVFigYRSY5NQZmZmZwYULF3DhwgXucslksqdITVQBFotF3Lp1C/F4HE+ePEG1WkWxWGTN0EajgXw+j4WFBRwfH8Pn8/HPodaowWBAq9XiIPi6OPcg2O12kc1m0ev18OWXX6JSqSCXy6FSqTz3YaR/Tg/t+vo6stksdDodXC4XVldXIZVKT2S+o9gCkUqlzMSbmZnB9PQ0V4HECq3X63jw4AF2d3cRiURQrVZHjvF1GrTK0m63UalU0G63R/6aAfC6QKVSQbFYRKFQgMPh4BdZo9GwVJpwf8lsNkOj0SAYDLJQwNzcHJxOJy/M3717F+l0Gvfu3ePVnmcleWcFGhtYrVZ4vV7Y7XYYDAZ0Oh1Uq1VsbW1hf38fOzs7yOVyODo6YimqTCaDyclJVCoVmEwmxONxOBwOBINB2Gw2GI1G2O12aDQafPrpp9jd3UUikeCAct4VoVBqS3gfqCV4fHwMiUTCq0cKhQLHx8cwGo3odDrQ6XSoVCpYXV3lvbJCocBqI9Qqpo7TqLXxTy+aSyQSfs5oJeBZXbRBXp9SqYTP5+P53/LyMmZnZ+H1eqHX6yGTyU4kme12G4lEAplMBuFwGPl8Hl9//TXy+TwSiQTv3dJ7ODc3x/NFYbel3+9z0ZPJZBCNRn8wnvwQzj0I9vt9XggnMVTKZH7o71G7LZVKodPp4ODgACKRCHNzc7w+IZfLR5JIMjExwYNdkq2iIEhtglgshkwmg8ePHyMej/N8dJReSAJ9x0KWHkm/kXjAqINeSHoGac+KNENVKhW3e4mhR4K/RMxyu91YWFiAw+GAVqtFsVhEpVLBo0ePEIvFsLOzg1KpxGsi5xkE1Wo1r3potVooFAqUSiVuBaZSKRac6PV6aDabrMRE1TwFyGKxyNU+iW8rlUoEAgH0ej2YTCZ0u903Omxe9fMJ5170h6oAYUVHBB+SjJNKpVzJUsuUlH2oNSyXy1GpVPg+dTqdc/9MLwsK+ELHml6vh1qtxuL8xMQexns3MTEBhULB0nwrKysIBoOYnp6G0Wg8IYBCusnNZhPJZBJ7e3vY2dlBNpvFwcEBJ6TCz0yqVLQGIeRJCM95Uqmi0cPrYiBBkHaVQqEQH56v8tDV63VmlVosFhwdHXE7aJSGwwCYcDA1NQWr1YqPPvqIHxRiOVEmdOvWLSSTSdy9e5dbwKMaTIQMNWJHVioVJBKJE6sDow5S7AmFQpDL5VhaWoLJZILX60Wv18O1a9ewv78PkUjEi71Xr16F0+nEtWvXWFmG1FYePnyIvb09/Pa3v0UqlUKtVmMJsvNMZhQKBRYXFzE7OwuHw8HSbtVqFalUisWyC4XCU+8akZhisRi7SjgcDiQSCa6QlpeXodfrMTc3B4VCgQ8++ABbW1uoVqsnGN3nAao0qBoVLlaTolQoFEIymcTBwQGvE9ntdlY0UqlUrJYDgAkX9PmootrY2MDBwQE2Nzc5sIwihEmMkH08SFBiaDKZ4PF48Nlnn/EcULgETxUgMZSJuPL111/jm2++QSwW4/kmtbTlcjnUajVbs33yySeYnp6G0+nkQgf4nodwdHSEWCyGvb091hkd2UoQ+H5eQu2hV22n0JdPGZ9wsX5UDl8KxiS55Xa74XA44Pf74XQ64XA4mGZfLpeRyWSQSCSQTqdRLpdHvpoicg8x07rdLiuRvE1uBN1uF61WizPQZrMJrVbLh6fL5eKZhdls5t1Ih8PBh7JcLuesPJlMIhQKIZPJsJD6eUMqlUKhUMBms8FkMnH1A4BF20nC7nnBmFrDtNpCAgKpVAp2ux2Hh4ccjPR6PdxuNwqFApRK5UB0fEl2S1gJ0nUfHR1xdbe3t8fzsXq9Dq1Wi1arxWIBcrmcV7TItaDT6fDeK/krxuNxbvOP4rNMxQQRtYbVBqWdb7PZDJfLBYfDAbPZzKxVuk8kL1mr1VgCM5VKIR6PI5vNotVqndiFpiqfdq5J0YkUxQgikQjHx8csykFV4Ju8dwNTjCFW0KtCJBLBZrPBarUiGAzC4/FAoVDwITYIGvrLXCO1LmZnZ2G32/GrX/0KbrcbV65cgVKphEajwfb2NiKRCNbW1jj7pGxoFF88AgV3ejhVKhVardaJ9tKw78HLgrLoSCSCfr+PaDQKiUQCn8+HqakpfPjhh3A6nbxHaDKZsLy8DK1WC41Gg263i1QqxS/0v/zLv2B9fZ2V7c8TdFCYzWZMT0/j/fffh9frhcVigUQiQavVQj6fRyqVQjKZRC6X+8F7QkGlWCyi2+1CqVSi2+1icXERZrMZExMTLC8nlUpxcHCAaDR6QknnrEHBiBiQp58tmm/u7Ozg66+/Zq1Wl8sFjUbDcyRqz1ksFjgcDhiNRtasJFUcr9fLs0RiBo9iIOx2u8jn88yCHUbFSixdEs9fWVmBXq9nXgYFwF6vx5UezZO3trbw8OFD7O/vv/CsEBY8z9uFrNVqrFdcKpX4nX5dDNVKiYIH9fMpOxX2+qVSKVdV1PYhcgMtMQ9rhiZUtdDpdNDpdJibm4PX60UgEOA9GWrbEi2fWG4KhYJV4UfZjV4Y5GnVhajaZBU1aofG80DPCmnQ5vN5aLVauN1uSKVSWK1WAN+1G4kQQ7Nnmqclk0lEIhFeP6AAct7fgTAI2u129mGTy+VMK8/n88hkMsyUfNlrorlNpVJhMfRarQatVgupVAqz2Qyr1QqHw4Fqtcrdi/MKgq1Wi9efKpUKVCrVibmQ8MClRWsKhq1Wiy14jEYjrFYrms0m6vU6i/jrdDr0ej12tDEajSfabqOG4+NjFItFlMtlrnwHDepAELud5tDPqtZp7Wt7exvxeBybm5svFF6gpIdYoqVSCQaD4ZkOLq1Wi9vyQmOF18XQgqBQJJb6/4eHh8jn85z9abVaqNVqXLt2DW63G0tLSxCLxSiXy4hGo3j06BGz1YYBCt5arRZTU1OYmprCb37zGywuLsLn80Eul59wyJDJZFCr1bBarbwqQmSYUbVSohYI6ZzSYZTP55HL5Xjm9LYEQaoyqtUqpFIpdnd30ev1MDMzA61Wi5mZGQQCgRMvNAWYZDKJZDKJe/fuYXt7G5ubm4hGoyiXywO5djL6nZ+fx/z8PGZmZnjXtFwu8+L41tYWIpHIK5FYqJ2YyWQgl8sRjUb53ZTL5XC73SgWi1hZWeF265tm4M9Dr9dDqVTC1tYWAoEAi0j0+32uOqjNKVy9SqVSJ36OSCRiPdXV1VX4/X6IxWKWyZPL5RwkXS4Xtra2RjYIEjGQ5mnDIPKQ2tJ7772HmZkZmEwmJo8JcXx8zCSYf/qnf0I0GsX29vYLn0Vq9cbjcYjFYuzt7fG9kslkJ/7barXKnQ7qBr5JUjC0IEhEC1ohWFlZweHhIavu93o9GAwGaLVaLC8vw2QysTLLzs4OdnZ2sL+/z8zTQYO0/cxmM2ZnZ7G8vIzl5WUsLCzAarVyKS+EXq8H8N1nL5fL8Pv9yOVyuH37NpLJJLa2tkZu1YAqVo1GA5VKxaSPZDLJ2q2nszDhHp6QuTtKMxfKOkOhEPr9PlZXV3F8fAy1Wv3U3JleNlLxv3fvHi/Uvwkr7XVBHQVhq6hSqSAWiyEajSIWi712q7JSqSAej+Obb75BLpdjZiyxFM9bqYSek2aziWw2i62tLf68VqsVFosFlUrlqaXx5/0sqihTqRSkUilyuRyUSiV3L6iCjEajI+nKQDg+PkahUGAPvWF2jYT3/jRr8/Q+rtAr9mVQqVSQTCaxv7+PiYkJXL169an/hqzc7HY7isUiFAoFdwReB0MLgqQE4XA44HK58O677+Lw8JAZpMfHx7BardDpdOzxRi4SGxsbzH5rNptDuX5a0XC5XHjnnXfw/vvv47333mNXDILw5uv1euh0OmYXxuNxJJNJHB0dcVUyKkGCQOoVwiBIGpsUBE9D2CamNjAlNi86tAYFkUjEs+RwOIzj42M+JN1uN3//RO/OZDKIx+O4c+cOotEo7t+/j2azOZQACHwfBIUtKOqORCKRNw6CjUYDX3/9NeLxOH7+85/z6gjd1/NmZBMTkuZ0jUYDOp2OLZ7Ib5R0a18UEEjXNp1OQywWI5/PQ6fTcSuXnDPC4fBIz7a73S4HwUHKRL4qThMWn1UpvghE5trb28PExMQzOw0mk4ndJPL5PLulvJVBkOYuLpcLi4uLmJycxOXLl/kLpMXlo6Mj1Go13Lx5E+FwGDdv3kShUBiagjrpLa6urmJpaQm/+tWvmMpLN5wOfQpqREDodrt8iJBizKeffgqdTodUKoV0Oj0U0eLnge6T0AaF5kfPCoDkhG21WnHp0iXWRyVK+h/+8Aek02m2gRk0qL1LZrkfffQRvF4vD/mFLy3diy+++AKRSAQ3b95EuVxGvV4fufktiUrXajXU6/XXrmgo8BP5IBKJsO3XIKskOkij0SjblZFhMHUi4vE47xA/D8Qr8Hq9WFpaYkWTXq+HcrmMvb09Jvu8ygz1PCGsqEbhel4FNI++ffs2e2tWKpUz+/n9fh+FQgHZbJZbosQ0fV0MLQieXgilIahKpTqRafZ6PRwcHKDZbCIUCiEUCiEWi73xB38T0HUTQWFqagoqleoEsYcqHmq7EK338PCQF7LJkWFmZgalUglut5tVLEYlIyUiD/0BwHs6pwO18HvxeDy4cuUK3G43ZmZmcHBwgHg8jocPHzLDbViLviQTRmoXPp8Pdrud1e7p2Ws0GrzjFI1GkUqlOPiPwr0RgogFtPbwutcnfFabzSavWtDzOKjPTb+LWp80DzQajTg+PkalUuGE5EUQPpMulwtOpxMWiwXdbpeJREQ4GXWW9iiD7hcRYsLhMCKRCLLZ7CtVaNQ5EsozCiESiXjfk8gxzzqLXgVDC4K0vPrgwQMUCgXMzMywsgrt85Ah6ePHj7G7u4u1tTVW6B9m755agtvb2zxHMplMMBgMiEajKJVK2N/fZ5V0au9SG2tmZoYX6fV6PbRaLfx+P372s5/xEuiotEVpT4zms9TfP72rJBKJ4Ha7YbPZ8G//7b/F9PQ0rly5ArVazVqUx8fHMJvNKBQKQ7mHZNNlNptx6dIlBINBvPfeexwARSLRiQrPYrFAqVTivffeg9PpRKVSQSaTwf7+/kCv+2Vw1tUDBT3hfaZ930HvqVH2XyqVkMlkAICXrH8IWq0WDocD09PTvA6hUqm4k0Qs2lFVanpbQFyBSCSCg4MDdvZ41fGHxWKB0+nE1atXMTs7i8nJyaf+G0pOK5UK37u3MgjSi1QsFiGVSrGzs4Nms4nJyUlmbAkNSSmQPGtvaNCg1iYx8vb29pjSGwqFUCgUsLe3x5JNdP3kDSYWi3F4eMiO3nq9HkqlEiaT6QTleBQgkUjYwuW0cgNB2GJ0u93wer1wu90soktZ3ek51qBAhA5h+93tdsPj8fCheHR0xMpGwl0lclagdYFqtTpyEn1nDaHLhlQqZYo6MUiHIdlFXR/635cN9sRsJhk4mlNT23dY6iuvilE5D54HWvEixjvNbF/2rCZxBGLz2mw2WCyWZ/IraK3s8PDwTETRh7on2O/3ua+bSCRgNBoRCATw4Ycf4k/+5E9gtVqhVCoRDAahUCiwsbEBqVSKVCr1xrshb3rdnU4HsVgMxWIR8XgcCoUCk5OT7K9Hqw/UHu33+3y4yuVytNttpNNpNqKkVQuifI8KlEolDAYDk3poXiZkgFG19+mnn2J+fh6XL1+GTqeDVqvlQTm112huNahDh0ydjUYjFhYWMDc3h+XlZSwuLsLpdEKv16Pf7yMcDiMej+PGjRvQaDTQ6XRYWVmB1WplfU6dTodyucxEnx9jIKTVJaVSCa1WC7vdzkvz5XIZGxsb7N02yHEEfdev+s7LZDImdVGCCYADIAnAjxKEjEthQjyMBPJlQYEplUohEokgmUyyLdzLQK1Ww263Y2VlBUtLS1heXubd3dOo1+vI5/OsQf2mZ8lQgyAAPkyoPSaXy7G1tQWTyYSFhQXYbDYWVfV4POh2uwiFQnyYDgskY0T/N8mJ0aySvOSEGTNVtaSYLizjTz/wowKq8uiPEHTNNF+jmQvpi1L77PDwkKtiYv0NAiTlZLPZYLPZeLeO/M4UCgXq9TparRb29/cRjUaxs7MDg8HAFSPpIZKrN4kDU6vwxwaaAet0OrZVIgFjyvSpehr1JIAIPWQdResv/X6f5eXoMB0lCL/XUf+OCUJNT6rQXoU8plAoWNmHhLNPewTS76hWq8jlctyVeNPvaOhBkA4T2vmhfu/m5iZ+85vf4MKFCywS/M4770Cn0yGdTjOba5jXTUSEl70O+qz0oLzsXGOYEA6pJRLJUztCExMT8Hg8WFxcxNLSEnw+H+v9kd0SiTrHYjF2WDjvSpAWpQ0GA65evQqPx8NC2B6Ph9sse3t7yGQy+OMf/4hoNIq7d+/CZrOxdBpVuTqdDhaLBcViETKZ7EcbBEnIeGpqij089Xo9t/DL5TI7L4xyC5EIMRaLBXNzc/B4PLy/S44M2WyWraZGGW8DW/R0EKTz7WWh1WoRDAaxuLjIHRhy2yHQ2UkC8UKHlDfB0IMgQagXWC6X0ev18PDhQzSbTSgUCuh0OphMJtRqNdhsNpRKpWFf8iuDBAKo0jAYDGyYSYy8UTtYSSibWIekImK1WpHL5U74idGDK/SBa7fbKJVKyGazSKVSTJA5T1DgnpqagtPpxMWLF+FwOODz+Vh5JJfLoVar4eHDh0ilUtjY2OCXigI+SXaR9B3NlYQ6iaMCoUDBq+xlEWgGajQaWQCCxhC9Xo/JTNS9GNXDmEB+dzMzM/D7/bBYLFCpVDg8PESr1UIymeRd12HtGv8QRjnonQadbbQSZbPZIJFIfrAlSuMKrVYLq9XKBEOhcwjwvR5pOp1m95OzEu8fmSAIgGdHtLD78OFD5HI5BAIBFsNtNpuw2WxIJBJvHUGBHLIpCBqNRmi1WgDff/ZRO2CEQfDo6IiDgdVqRT6fh9VqRSAQwMrKCsxmM1QqFf9dqpaFQfC8tV6JBCOXyzE9PQ2/34+LFy/CYrHA4/HwnJb2jB48eIBEIoHNzU32GKS2NAVBj8fDknfUDn2dQHOeOK3Q8yqgljeR0lwuF4LBIGZnZ6FQKNDv95HP51GpVEbyGX0WVCoVgsEgr8DQs0mCG8lkEul0GsVicWiiB28rnnXvietgNpvhdDpht9t5xeVFwXxiYgKTk5NPBUGhIwUVSJVKhVfkkskkB8E3xUgFQQKV1alU6sQqwqVLl6BSqTAzM4NCoYBIJIJSqXRmmZxIJGImpMvl4oBM6iCv+/LTA0IzsytXrmBmZgZTU1NQKpX8Um5vbyOfzw+d/SoEZV/JZBJKpRJ+vx9GoxGrq6tQq9UscDA7O8uO0sSeJRfz/f19RCIRxOPxc50HUgAgm5zV1VXMzs5ienqa3ceJhHX79m3s7+/j3r177DJPKiLtdhvlcpnnl6NyL14E0nUkEtPLtpzJnJeMTJeWlhAMBrGysgKn08nWX7dv38b29vaZHTznAUqAjEYjPB4P5ubmMD09zQFwYmIC+XweyWQSjx8/xsHBwUA6Ez8WUEKczWah0+ng8/nQ73/n9E6sWzoHisUiu43U63VUq9UTHSKxWMx74S6XCwsLC5iamoJerz8xdhF6Em5tbeHzzz9n5v1ZjZJGMghS5kAfNJfLwWAw4Pj4mJfM6YVvNBpnEgTpAKWsZHp6Gu12m1tfNAN51QORHhBagXC73Sy2rdVqIRaLWZsymUyOnHQTMeiI9tzv9yGXy2G327l97Xa7YTKZTtDP6f6RdyI5EwzCbkihUPB+GDFAxWIxu4+QGevu7i7i8ThqtdqJg51mD6eDyKjMZZ41I6JZnkajYQLIi9YYqHKUSqVQq9UwGo283kKzQJ1Ox04OoVAI6XR6pIMGfSaNRgO9Xg+z2czO5PRsEucglUohn8+fmxPGjxFUnNCOHu0+UwteLBbDYrFAKpWyWPnOzg4mJibQ6XR4XQoAa8HqdDr4/X4+Q4TjBiGxrlwuI5VKYXd398xF+0cyCBJoTpbP52EwGNDpdCCVSjE9Pc0mjaQc8aYgw1iaIfyP//E/UCqVcOvWLTx8+BDr6+tMp37ZL5/k1UwmE/x+P65cuYILFy5gdXUVZrOZs+xbt25hbW0N//iP/8iBf9gHLYGILI8fP0az2cT8/DwsFgvbRAWDQWg0GkgkEq4Am80mcrkc7ty5g42NDdy8eZMdoM8rCJLdk0wmg8/ng9/vZ0PjiYkJ1Ot1HBwcYH19HXfu3MGdO3cQiUROUKzpEDUajbDb7fD7/fD5fJicnOT1DrKOGuZ6DtkC1et1yOVyFgBYWlpCMpmERqNBrVZDtVplbU3hOgMpFmm1Wmi1WiwsLMDv9+Pq1atcPQHfLSWvr68jFArhyy+/RDqdZoWOUcXExASv5wiNXulQpaQsFAohm82OdGt31FYims0m8vk8vvzyS+TzeVy8eJGdfug6yV/w/fffh9/vh0wmQyQSwZMnT6DX65kDIZPJWFYxGAyyJJ5CoYBEIuHd6kKhgEwmg2+++QZra2t48uQJn8NnlbycWRAUDubPUmKJsgHK2MRiMSYnJ6FUKp9yHX4T0EyEaLrT09MwGAwoFovIZrM4ODjg9Qfhi3OaLSnc6ZHL5bDZbLDb7TybmJqa4qBBChihUAjxeBzFYnFortHPA1VE+XweSqWS1Ww0Gg0TlqjFQWsf5GlHYs7pdJpJFecBoQSfRqOB2+1GIBCA0Whkcd1qtcouC9FoFMViEY1G48TPETIKg8EgnE4ndyDI6oq8H4dxj2g2Uq1WUSqVWGiC2tBGoxFOpxPtdhsOhwNyuZwFl4VBm3bmKPumwOf1ejk7r1Qq6HQ6SKfTSCQSyGazqFQqI1850Ry62+1y+004v6WEgGbcoxoARxFUlWWzWZhMJlQqFZ7pUUVIVZzRaAQA+P1+SKVSHB4ewmQysZOOVCrF7OwsDAYDPB4PlEols0FpHafT6aBQKCCdTrM5L9lInWW37EwiiDALn5ycfCpYnOUF00FFX9qzlilfB7QQfeXKFczNzTFN3uPxAACy2Szv+VEWQkGPDmFha4DMT3/zm98gEAjg+vXrzAilbPTGjRs4ODjA//t//w+lUmlkZy3Hx8fY3d1FOp3G0dERvF4v/uRP/gRTU1OYnZ1lJZ9KpYJKpYJvvvkG4XAYf/jDH9iB4TzboMKEY3p6Gv/u3/07fPLJJ9BqtXztW1tb+O1vf4udnR1sbGw8dT2UXJlMJvz85z/Hf/2v/xVTU1NQq9W4c+cOwuEwtre3EY1Gh6Z7Su3n9fV15PN5eDweBAIBbuF7PB588MEHmJ2dhUqlQjqdxpMnT9glgYI3SRT++te/hsvlwsrKCtRqNbfnhe4KN27cwN7eHsLh8CvT3geNXq+HVquFzc1NJvvQuSRUHnlbMAqtdyG63S5arRZisRhkMhkePXqEqakptlsjiTOxWMytaJPJhHq9jkKhAJvNBpPJxD+PZn+nLdd6vR53+G7cuIHt7W381V/9FY++zjoJe+MgSDMveokMBgOq1SparRa/NI1Ggw/KV4XQkZ0yOrLNaLVaZ/ZS0gNH10kvEVl2LC4u4ujoCAqF4kQ/XOiyQE4LUqkUGo0GBoOB6flkDEqu7JlMBgcHBwiHw0zCGGV0Oh2IRCLE43EcHx9jfX0d3W4XVqsVpVIJtVoNsVgMhUIBa2trSKfTrPN63hm3sBJUq9VQqVScnXa7XWYEEuv4dEVKAdDhcODatWtYWlri2Ua32+WZKOndDvNgooO+WCzi8ePHODo6Yrk6eg/FYjEWFxfhcDhgMBhQKpVYwaNarWJ1dRUul4tXB6iSlEgkvOOVSqUQj8eRSCSQy+XeCmkxAr3DwiR1jDcHBSjiCUSjUYjFYhgMBhiNRo4FVA3S+UnrNyQP+SLQKlY8Hkc6neZ2PBGyzuMZfOMgSG7XREEPBAJIp9MsbtpqtZgVKJQQe9mfTYcb2SoJ/cTy+fyZsQ2p/Baq1lPgXVxcZMYhyWtRQNRoNNzyJAshrVYLr9fL2REFcWrrxmIx7O/v4+bNm0gkEtwGHWW02210Oh1sbGwgGo0il8shl8vBbrfj8ePHCIVCuHXrFjNJKUkZBMlH+MIJ6dU0o8xkMshms8/0YqNkh9ik//t//2+eebZaLV70TyQSyGQyZ2oL8zro978zgm21Wvj7v/97HBwcQCKR4NKlS7ynRUGRCD4kQvH48WPs7OxgdXUVNpsNHo+H2dAUKJrNJiqVCh49eoSdnR08evQIhUJhpOeAPzYIg/coBXAqEur1OrLZLO7cuYNisYiJiQn4fD5mfJIqj1gshkKhYKLay6wVEXHp7t272N3dxd/+7d9yl+y8zpE3CoLUhtLpdPB6vVhdXcX777/Pmm7lchnFYhH//M//zLM1oZTYi1qlxPIjTTm73c7LrsViEblcDplM5sx0/zqdDur1OpLJJHQ6HdrtNmc1QvNcn8/HC6BkDEyKIlqtFhqNhv8Z/X1Sq8/lcsjn87h37x5b85DA9ii1PZ4Hms+SLFy73WY7mng8jlwuxzZJNDsaxOei66rX6xyc8/k8a176fD5IpVLU63XEYjGEw2GuTm02GzN35+bmYDabeZ2C2p937txBPB4/03WcNwXJ9uVyOTx48IAX/BcWFmA0GiGXyzn5Ik89v98PlUoFt9vNAgBEFqHDJ5FIIJVK4caNG4hGo9zFGWMMwvHxMZrNJvb391m+cmlpCYVCgZ8tGlVRgvVDkpA0aqpUKkin02zFRGfJeZ4jbxwEiYwwNTWFlZUVfPrpp/xh8/k8UqkUe8lRi5TsNUjJnYKh8OeSiK9OpzsRBI+OjlAsFpHP55HNZs80CPb7faRSKej1erTbba7i1Go1qxpQu0hYKdIBRP9LbVKRSMTtq0gkwgae6+vrSKVSyGaz5748ftag6oICYLvdRqFQQCKRQKFQOHPm1suAKj5hEMzlcpyQ+Hw+6HQ6SKVShMNh2O12/t4XFhZYJ5OMdimobm9v48GDB7h//z5yudxAVjxeFnSNhUIBjx49YjUbi8XyVAeCDiOpVMq2UTSPOTw8RKlUQi6XYwucUCjEtmXnMYMZ4+1Gr9djf1ea+dO8jggwdrsdSqWSnWd+qKoVLsSTLGY0Gh3ISs4bBUEaoGcyGdy7d48FaT0eD8xmM9xuN5xOJ/7bf/tvPBylijAWiyGfzyMcDqNWq/GSuFgshlqthk6nwyeffIKFhQV89NFHPNuIxWJ4+PAh9vf3z7QdSusY6XQaExMT+Pu//3vMzMzg2rVrPGCnMv9ZAZsylUajwQ4RjUYDyWSSNQpTqRQymQxTzc9ypjlIUCLy8OFDAGDmFjEKB13VUkCoVqsAgBs3bqBUKuFP//RP4XA4oNfrYTKZMD8/D5vNhpmZmROVILUEe70e9vf3mRH51VdfYW9vD4lE4swkms4anU4HuVwOjx49YmEDi8XCGbnb7eZEUi6XQyaTIZ/Po1arYXd3l70vaXcul8uhUCiwUMU4AI7xLFAgJBk64gGsr69Dq9UiEAjAarXiypUrbI/0IpTLZcRiMdy7dw8bGxt8Xg7ifHzjmeDR0REf9jQQrdfrcLlc0Ov10Ov1mJubY2ZbLpfjlmMikeADleSYaE/LYrFgfn4eFy9ehMvlgkQiwcHBAf990vw7q0OJXnYKyBsbGwDA0lHCjEYIIZmG9O3q9Tqr2ezv7yObzWJvbw/FYhGlUmlonmxnBapu0+k0L/tTBTiMz0SJSafTQbVaRSQSAQBcvnwZk5OTUKlU7HYxOTkJvV7PRA9aVxGJRBxEaJE+FAohkUigVqsxLXvUQMQzGjX0ej1mIBsMBl4Z0Gg0/H6WSiXk83lsbm4il8the3sb1WqVgyPtIY4qW/nHDqEQgnCHlYTsKeke5tlBiSd1htLpNJrNJrLZLJRKJau8OJ1ONh5/EagVH41GEQ6HB2q8fSYrEhTIqAJ68OABy5sZDAYsLCzAZDIhGAxCr9fDbrdjfn4enU4H+XwezWYTmUyGK0FiVlIgpZ2oL774ApFIBOvr6ygWi2f+EBDpptvt4l/+5V+wvb2NSCTCNOuX6WlThUfadpRRFwoFbqWe5R7lMEAMsUwmg2KxyPO/Yc42aUbW7Xaxs7ODdDoNhUIBu93O2pFzc3NMZCLSViqV4vZ8MpnEN998w3PDbDbLCcsoBkDgZFuULGYmJyfx5MkTqNVquFwuGAwGOBwOTuKItUvBL5PJ4PDwkNvY9GeM4YCCHyUjx8fHUCqVuHbtGgwGA1qtFmq1Gur1+tDvExUBxDwmohkJnMRiMbZaexGKxSISiQTC4TB7zL6KMMmb4EyCIM32ms0m75KQK7xer4dUKkW1WuUs3Gg0steXRCJBt9uF0Wjk3TvaO5FKpRxQstnsCTLJeWlQUsWaz+cBgBUMTtsInQYFNWoRFAoFtFotlvghgsGwH9qzglDEYFRALyTNscLhMCucVCoVqNVqmEwm9Pvf+Vc2Gg0kEgluSyeTSX7G8vn8W2EZRKC9XKrSqT1M5JlCocBBkAg+qVQKzWYT1WqVCWtjDB90nlarVRQKBRZoMJvNKBaLUKlUvLI0KiYCwhU4sVjM3T2S88tmsy/8+9SBowRtkO/dmSnG0JdAB75IJEK5XIZcLkckEmGWp8PhwNTUFFwuF8tTqdVqptgSQ4j2oNLpNA/pt7e30Wg0UC6Xz21YSp8jm80in89jZ2cHAF6aqnxa15Ee0FF4UH8qIObqrVu3TqwN7O3twWQywWKxsDB6PB7n4XuxWMTm5iba7fbA1jvOCpQAtFotrhREIhFCoRDPrYX/rZCZ/bZ8xp8KSOFobW0N1WqV164CgQC63S42NzdZ3H8UE7Rer8ejH3L7+aHz8/TzOMhn8ly0Q+nGUDQn2jxR62n/ymAwoFAoQK1Wo1QqnQiChUKB9f1ovkaSOYPQ+xPO+sZ4+0DtUWrVkPg6iTqQQwTtIBHJi7oZb1MAfBbGwe3tBZH0MpkMJiYmsL29Db1ez4IPo+g7ehqnZ5qjjHMV0CYtyVarBZFIhFQqBZVKBZ1OB4PBwOr1RO2mgW+tVkOlUkEqlWKJMaLjj1/sMV4W1K4lDcJQKDTsSxpjjB8EEU729/eRSqWYIyGRSNgMehSZym8rRC/6IkUi0Zl+y7RXKJfLWeGd9peUSiX3t2mXkEgJjUZj5OZPY4wxxujCbDbj3XffZQNr2tsNhUIoFAp48OABms3mme0ZnweIDTo9Pc3iB6TpSi3/t6HSGgX0+/3n9mMHGgTHGGOMMcYYY9B4URD8YTG3McYYY4wxxviRYhwExxhjjDHG+MliHATHGGOMMcb4yeJc2aFjvL2g3TJy5ybJLZlM9lxFeJIiI4UVoanyqIJ2mEj4nDRiJZKTrwYRtmiRWfjPATBlnfRlSZv0bWLwiUSiE84TtLJECkFv02f5sYLukVQqZQ9IsVjMkoWtVmvYl/jWYRwEx3gK5OGoUCig1+uhVquhVqsxOTkJl8sFmUzGbDsKhv1+H7lcDvV6HeFwmBe2afF8VEGHiclkYsssnU4HvV5/4vOR0Wyj0UCxWOS/T3R2Eu82GAxsLyV0HBl10OGq1+uh0WhgtVoxOTmJVquFer2Ovb093p8cY3igXVen0wmXywWr1Qq5XI6dnR0Wexj1HcJRw8gGQao6yKWdHNyB7w7cdruNZrPJ0lbjG//moINQqVRCq9XCZDLBarXCYDBAp9NBoVBgamqK3QioIiQ1EjJTlkqlbIlSLpdHKggKXeglEgl0Oh2USiU8Hg9MJhP8fj9MJhPMZvOJirfT6SAcDrPWJuHo6Ajdbhf5fB4ikQh2u50tl0jb8W0QSpdIJJicnITNZoPT6WSd1XK5jHQ6jVgsNvJV/Y8dYrEYk5OTsFgsmJqaQiAQYHcQUukaJRPetwUjGQTpMCaT2pmZGbaDEYvFOD4+Zh+rWCyGUqk03pk5A4jFYsjlclgsFjidTgQCAXi9XjgcDhiNRqjVani9XkxOTkIul3OblMyD4/E4CoUCDAYDMpkMNjY2EIlEkMvlhv3RGGSLRcFvamoKBoMBS0tLcDqdWF1dhd1uh9Pp5BYw8J0U28bGBtt5UauTqj2Sh/L5fKxHmslkTrSGRxkymQx6vR7z8/NYXV3Fz3/+c9hsNsRiMWxsbODGjRsnDLHHGCzIRUKn08Hv9+PSpUu4fPkybDYbZDIZms0mpFIpbt68Od6nfkWMZBBUKBQc/BwOBy5dugSLxYLp6WkOgmRSe/PmTQBgl4ZxIHw9iEQiqNVqDgh+vx8XLlyAyWSCTqfjYJBMJvkQpNmRVquFUqmEVCqFyWTChQsX2EWD2oSjAJFIBJVKBYPBgJmZGdhsNiwuLsJkMnGi5XA42HoJ+F7+SSwWw263Q6/Xw2w2nxCr7nQ6sFqtEIlEcDqdUCgU2NnZYVk2ErceVYjFYuh0OszOzmJhYQGLi4uw2+3Q6XSoVCpQqVRsGD3GcCCRSGAymeB2u7GwsIBAIICpqSlMTEycMLkeJyivjpF8qhUKBbem/H4/rl+/DofDgUAggImJCXS7Xezu7kKv1yOZTKJcLqNWq721Lg3CFsawHmIyMzaZTJidncX8/DzeeecdVvQhn7lYLIZ2u43Dw0OuAi0WC/R6Pc/TqJUWiUQQjUaH8nmeBZFIxBJ9s7Oz8Pv9eOedd2A2m3nWKZfLAXx/H0hDViQSwWw2888iBSNSNbJYLPzf9Ho9WK1WFAoFbhuPKqjrQhXGzMwMgsEgTCYTezEqlUomYJyna8GbtvJ+zAFgYmICRqMRDocDwWAQXq8XTqeTHXVIk/nH/B2cF145CArZdMD3mfKbluD0M5VKJYLBIC5duoT3338fgUAA09PTUKlUmJiYAPDdA+HxeKDX65FKpSASidBqtVAsFkdWWf00yDxYpVLB5XLxQUnq68Vi8dzsok6D5q/Ly8uYmprC6uoqlEol4vE4stksCoUCtra22POLWoBUCTqdTlgsFnz00Uew2+2wWCwol8tIJpOoVCoD+Qw/BIlEAoVCAZ/Ph2vXruGDDz5AIBCAzWaDQqHA5OQk3wNqXwpJL6SDS4dMvV5HvV7Hzs4OWxVNTEzA5/OhWCyyBc6oP4sqlQrLy8tYXFzEJ598gvn5eXg8HkilUhwdHaFWq6FWq3E1e5aHrFgs5uRLoVDA6XS+drVJNmZHR0fswfcy3z3xC8g1ZBTvl0KhgNFoxDvvvINgMIgLFy7AbDZjcnISe3t7iEajuHXrFqLR6Eh3HEYVr/zE0RyIMlw6MN7kBaFsVC6XQ6fTwWazwe/3w+fzwefzsSeh8L/XaDRQq9Vwu93IZrPY3Nxkd4pRB5EzSEh8ZmaGAzzNm8jNfBAQi8Vc0VksFmi1WhwdHSGVSiEUCiGZTOLhw4fs90VkEFqhqFQqKJVKCAaDkMvl0Gq16HQ6zA4dBVDb1mazwev1Ynp6GlNTU1zlCEEGs51OB0dHR8jlcpxt0zNerVZRqVSwtbWFVCrFQZAy8kql8lbYMclkMrhcLng8HkxNTcFisUCj0aDT6eDw8BD1ev3cnDXo+dFoNDz+kMvlr1wRUiJObjWFQuGl/BHp7xGBiZ7rUQqEIpEICoUCWq0WbrcbbrebEzfgu2Qsn88jlUohl8uN3LWTKQIwus4mrxQEqZ2kUCjgcDggl8uZQh2Px1+rHUl7STqdDi6XCx988AGWl5dx5coVrvZelB2+++678Pl8yGQy2NnZYWucUc6IqOK9fPkyvF4vfvWrX2FiYgLHx8e4c+cOHjx4gEqlgnq9PpDrMRgMMBgMMBqNEIlEWFtbQygUwr1791Cv19FqtTjLFu6/UQKk1WrhdDrhdDphs9k4u6ZAMAqw2+34sz/7M1y4cAFXr16Fy+WCUqnk5IM+0/HxMba3tznoV6tVrK+vo1wuo1gs8vNNh6zwexGJRHjw4AF6vR5Xy6PsSg8ASqUSS0tLmJ+fh9frhVarhUgkQrVaRbFYxN27d7G1tcU2ZmcJuVwOpVKJlZUV+Hw+/Pf//t+h1+tfuX1Mz+H+/j6KxSJ2dnZ4RvYyfy+ZTCIUCiGfz6NWq7Fg/7DPEGGHxufz4f3334fT6YTdbmf29f7+PnZ3dweaNP8QRCIRGyRotVq2hmo2myPZsn3pIEhRXalUQq/XY3Z2FhqNBtVqFfl8nh3UX2UvSiwWQ6PRMEXd4/Fgbm4OU1NTMJvNz8zST0Or1aLf70Oj0ZxoaY0yaJZmNBphs9lgt9t5wG0ymWAwGE5UvucNOvzL5TLa7TaOjo4Qi8WQTCa5GqIqQHigy+VyqFQqmM1mJlIoFAo0m00mxQy7EqTdN6oAnU4nz7smJib4IKR1m1wuh83NTWxtbaFQKKBareLg4ICrXXq2hd+HMMNtNpsn/vmoBkB692gNhizNKBmr1Wrc/s5kMudSIVFHSafTwWQyMfHoWe/w6epQ+P9TG7Pb7fJ+J82tXwS69zqdDpOTkwiFQsjlcjg+Pmaj5WGCXHZob1Wn0zFJ6ejoCJVKBfl8HrlcbmT2UYXMfmKTdzodVCoVZku/6Ht9VhfgvD/XSwdBal1MTU1hZmYG//N//k9MTU0hlUrh0aNHyGQyKJVK3Ir4oReGAsHy8jI8Hg/+9E//FA6HA3Nzc1CpVCdmgEL0+/0TX5RKpeIKlYLgqO/KyGQyqFQqeL1eeL1eWCwWAEC73YbFYmGGokQiGQjduVqtotls4vPPP2f2LbWWX9TCsFqtWF5exocffoilpSXMzMxAIpFgd3cX+/v72NraQrPZPPfrfxGUSiU++eQTzM3N4f3334fdbofZbObkigL2w4cPsbm5ib/5m785MQfrdruo1WpMhBmFg+ZNMTExgcnJSVy/fh2BQADLy8twOBzcBq3X6zg4OMDBwQG+/fZbJJPJE/PQswK9B9SGp4rhWe/v6Z1U4ibQP5+YmIDX60W/38fy8vJL/X5KUsrlMvL5PP7whz/g8ePH+Pbbb5HP5zn5GzTocxmNRuj1elgsFphMJiiVSshkMvR6PRQKBezv7+PRo0d48uTJ0JNNAu2bLiwswO/34z/8h//AieWXX37JZ8rp71V4f4VnOMWS80xIXjoICvvnhUIBm5ubKBaLyOVyODg4QLPZ5GzkRS8LzRSNRiN0Oh1WV1cxPT0Nr9cLo9HIi/G0o/WiDJD+f/rSRj34EchoOJVKQa1Wo1wuc/tApVJBq9VCoVBALpefORnhWaDfUavVmP33ItmviYkJKBQKWCwW+Hw+uFwu2Gw2HB4ecuVELNJh7izR9zk9PQ2PxwODwcDVjkgkQq/XQ7PZRKlUQjgcRjgcRiKR4CqCXkBhJfxjwOTkJDQaDc/ciaAlEolweHiIWq2GbDaLdDqNUqmEer1+Lp+d5sahUAjHx8d4+PAh1Gr1M99jrVbL7VNKyBUKBV83gGcmzS8CPd8ajQYAuNIi6bxhgwKKw+GA0+nk74ZmgNFolFv2w65a6fylTtbi4iKmp6dhNBo5yX5eIkVJmUqlYoUqiUSCfr+PYrGIZrOJbDZ7bu/gKwXB4+NjZLNZtFot/M3f/A1UKhXq9TpKpRJnTj90aNON9fl88Hq9+JM/+RNuU8nlch6Mv0xAowP7bQqAwHeL18fHx3j8+DFarRbm5uZgt9sxNTUFvV4Pq9XKL+Qg2jLUTqrVai/130ulUlitVvh8Ply8eJFb2Lu7u0gkErh9+zai0ehQ+//UHTCZTFhdXYXX64XNZuM2KD3PpVIJqVQKDx48wO7uLhOTfoyg90StVsNiseDy5cuYmZnhdw8At4TD4TD29/eRy+XOjWxWr9fRaDRw8+ZNbG1t4fj4mIPc6ev2+/0smCGXy6FQKGA2m6FSqd7oGmh3lCQChUn4MEHzQKVSibm5OczMzMBsNqNeryMUCmFrawvr6+uIxWLcfRv29UokEkxPT2N6ehqfffYZbDYbDAYDIpEIMpkMGo3GU4GM/p5Op4Pb7cbs7Cw8Hg+USiV6vR4eP36MVCp1rvu2rxQEaTm41+shHA5DJpMxa44W1Z91gNAHpZfP5XLhypUr8Pv98Hq9TPeVSCRP6VFStk5VhlQq5ZnZIOdmZw2RSAS9Xg+DwcAUcZoB0Ev5Oky58wbNkhYWFjA7O4upqSmo1Wr0+33k83kkk0kkk0kUCoWhBhN65mQyGWufCg83oeILkXgajcbQrncQoLahzWaDx+Ph1ZbJyUkA3yVnuVwO0WgUkUgEsVgMR0dH53Y9p+eoDx8+hEwme+Z1h0IhZknSfaXK4UWf1el0wu/3w+VywWg0PvX7u90u9vf38fjxY9y4cYNXXhqNxlB3dsViMas2ORwOGAwGdLtdVCoV7O/vIxQKIRKJ8DrIsBM3rVbLggt+vx92ux0KhQKpVArhcBjb29soFApPxQgKgE6nE8vLy1hdXYXf72dm8sbGxrl3YV6JHdrv95kocXh4eGJF4kXzEtJq1Ol08Hg8WFxcxJUrVxAIBJilRwHw9O87Pj7mjDGZTPLsD8Az/87bAlrzIPkuSgIoy5XL5SxSPSoQJjNCSTWFQsFVVSaT4fnwMK9TqLavUqn4+z2tBNPtdtHpdNBoNEZmrnJeoNGByWSC0+lkQoxMJmPVESLDxONxpFKpc29n9/t9TqK3traeS2yj+0erWdQSpQr2NIh0c+nSJRwfH0Oj0cBgMJz4b8jxZH9/H7/73e943YV2dIfZxaBkxefz8dpSt9tFtVrlBCWZTHJ1NWyo1WpYrVZ4vV6uWo+Pj7G3t4dEIoFQKPTMrtbExAQ0Gg1sNhuCwSCWl5cxNzeHXC6HXC7HYwvg/Agyr7wnSHMS4Rf/ojkgfUij0YilpSWsrq7i+vXrmJmZgdVqfSoACrPzTCaDcrmMnZ0d1Go1lMtlnj/RTOBthnAQTAH/6OiIWbajRMQgV4mLFy9ienoaly9fhlarRT6fx/7+Pmq1Gu7evYtoNIpGo3GuFcQPgZ5HCm6ZTIbXekj3VMh2NhgM8Pv9mJyc5H2zYrH4o5kFUlKgUqmg0Wh4Od5oNEKhULDYRDab5aw9EokMJAgC3zNtX7QSRALRwvm/kChDkEgksNvtMBgMCAaDmJ6ePrFXR0l7vV5HrVZDNBrFgwcPsL6+zgLww2KGUmA3Go0wmUy4fPkyLl++DKvVColEgmg0inA4zGMHahEOE3QfaMWNOgz0TJHgxvOCtUwmg8PhYMKlTqdDv99HLBZjacx0On2u1e5ryTPQgf2DP1wigVQqZUcCl8uFqampE9mNUKWDSAjNZhO1Wo0XQOmQPTo64l7x234wAU+TfIRBkJiJwwY95ESmmJmZwdTUFKxWK1d/iUQC2WwWsVgMmUxmJDRcqcprt9solUowGo3odDpcPdDnojUPq9WKfr+PRqMBiUTCO37CBephf6Y3AZGZtFot7HY7XC4XFAoFExCOjo5QrVZ5vk9khkGBruF5EP67Z5HjqEtBvAKNRgO73Q6TycRzPgDMQK1UKigUCohEIkgkEsjlcizuMKz24umxERFi5HI5ut0uisUi8vk83x/aQT1PKbsfAgltkO6wTqeDWq1mhnmxWES1Wn3uWUYiFnq9nrsSQsZuqVRCrVY713fv3LRDRSIR9+EvXrwIp9OJy5cvw+fzwe/3nzDtJGmqUqmE/f195PN5pNNpRKNRFAoF5HI5iMViLC4ussQVPdR0OL3tgZEkqnK5HOLxOPL5PCqVytAH3nSo0MD6v/yX/wKNRsMec/fu3cPOzg7i8ThyuRwrrQz7XlBAy+fz+Pbbb1Eul+HxeGC1WplRODExAZPJBIVCgU8//ZRtkvb397Gzs8NCAbFYDI1GA6VS6aWUSEYNJM7g9XoRDAZx9epVLC4u8k5ep9NBsVjkWVM0Gh3p1vCziBUymQxzc3OwWq24fv06bDYblpaWeA9SqVSi3++jXC6jVCrhm2++QSKRwP379xGNRrkFOsz5GtmYeb1eXLlyBfPz83C73RwQbty4wasr5XKZkzgAQxNl0Gg08Hg8WFlZwYULF+ByuaBWq1k3+NatW4jFYs/8u/R5p6am+A/NPQ8ODrC1tcUCBm9dEKQK0Gq1wm63IxgMwm63w+12c7QHvp8HdDodZLNZZLNZbG9vI5vNIpVKIZPJ8BegVqthNpthMBiYwiwSiXiWQQoPg36A6YAhlX26DmKAPuvApLYHCTbTzlqn0+G9NapChgHhTE2pVEKtVnMFb7PZIBaLWSosmUwik8mwoe4oBQhqrScSCej1ehSLRSiVShiNRn5+yKfSarVCrVYzRV6hULBouFgsRrFY5PmhcCH+bQBl68Su1Ov1vIfa6/U4wKdSKc6+h91m+yHQqhWxzScnJ+F2u+FyubjTRPeUZp50zhD7NZFIcKL9ImLfoD4PkbhIKFuj0UAmk7EgSS6XY21kuVwOg8HARC/qlA1SoYnGCVarlf9IJBIcHR3xGZ7NZp/LLqYzkBbrFQoFdyDK5TLK5fJAdjXPJQgSU4iWcX/5y19Cr9fDZDJx+5MCRCwWQ7FYxKNHjxAOh/HFF18gl8shk8lwlre6ugqbzYaPP/4YDofjhLUPqSbQlzfoB1mv12NhYYEXWmmvanNzE9VqFeVy+anrEbbgLBYL1Go1rygUi0VkMhnU6/UfVLw4D1DwI3q2x+OB3W7Hn//5nyMYDMJisSCbzeL+/fvY3NzE+vo6isXiS69XDBqtVgt37txBo9HA6uoqkyRo8ZiISFqtlv8OdSdarRYajQZ++9vfIhQK4caNG2wy+zKyXKMCiUTC4gwXL15kNrZYLEar1cLBwQEePXqEr7/+Gpubmzg4OBjpAE/msrRTS76jv/jFLzAzM4OlpSWoVCp+r7rdLrLZLIrFIm7duoV4PI5//dd/RT6fRzgcHnoXiSo6nU6HqakpLCws4MqVKzCZTACAnZ0dXllpNBrQ6XSstyqTydDv9xGNRlEul3nn8rxB98DhcOCdd97B6uoq5ufn0Wg0kM1mcfv2bYRCIezu7j7zHCPhdIPBwCxltVrNhJhIJIJIJDKQZOxMgyANqmkNwuv1wuPx8M4b7WfR2kOr1cL29jaSySTW1ta4+iPaL60KUEVpsVg4AFIfPJ/PcyAlO6XzfqApAzUYDHC5XJifn+frS6fTKBaLSCaTXNqfvh4hxVulUkEul7OSPcmNDauiooebhMzn5+d5p9NsNnOLMRqNIp1Oo16vj3zV0O12USqVsLa2xubL1JXQ6XTMwhUSlahSFIvFmJubg1arRa/XQyaTwdbWFnK5HLLZ7Mjbd5EwPc0CfT4ft4NJDWdnZwcHBwdIJpPn3np6U1D1rtFoYLFY4Ha7OQh6vV643W6o1Wo2fW6320yAicfjePLkCZLJJO8/DnvcAHz3zqlUKraP83g8sNlskMvl6PV63OmyWCwwm81cBRqNRkilUvR6Peh0OqTTacTj8YF0KUiOkGzItFotJiYmOImPxWJIp9PP3e2jfVUyQpDJZCxfSFVgtVodyLN4pkGQKgi/34+VlRVcvHgRLpfrhBYmERZoMP3VV19hZ2cHt2/fRrPZRLPZ5CBBw9KZmRkEAgG43W4olcoTg/FoNIr19XWeo513+UwvoVqtxsLCAmZmZvDxxx/D6XTC4XBgb28PyWQSBwcH6Ha7SKfTT/0MasGRcLVKpUKn00G1WkWhUEA2mx2aGC6xeV0uF5aXl/H+++9jeXmZFf6JOUhSeaMwt3wZZLNZ/MM//AMODg4Qj8fx3nvvIRAIMMtYuD5BzxeRFK5fv45ms4lAIIBQKASVSoWNjQ32chvVoEGdFJImCwaDuHz5MrfQms0m8vk8vvnmG+zu7mJ3d3ekq1vqUkxOTrIn5MWLF7kyWl1dhdVqPXHW0GrVw4cPsbGxgS+//BLZbJadI0YBExMTMBgM8Hg8uHr1KgtmU1Cg3exgMAidTgev1wu73c6jiW63i9u3b2Nraws3btwYiBOGTCaD0+nE9PQ0ZmdnYTAYIBaLEYvFsLe3hydPnqBQKDw3QaZVHYvFwizlw8NDbsun02nWcT1vnGkQpLldMBjE4uIiixXTCoSQtv748WPs7e3h4cOHTDwgJX4S9iVd0XfffRcul+vE3hy1MFKpFPb29lAoFM5N3olAs05iR3788cdwuVwIBAJQKBQQi8W83vGiGSXNnORy+QlLqkajwQShYVVXVOE6nU7Mzc2xmg8AlEol/NM//RN2d3eRTqcHVnmfBbrdLhqNBqLRKFdA6+vrCAQC0Ov1mJqa4mrptBAD7Rp6PB4WiKDOxt7eHvL5/EjNQglSqZRn8p988gm8Xi9XuMfHxzx2ELINRzWhoXui0+lOrFt98MEHvGer0+lOKL3QiCGRSCCRSCCVSrE2qdDiZ5igpJpE3gOBAC/112o11Ot1trciYQ0id5EEYK/Xg8vlQrVahVKp5PWq8wJVrvPz8/D7/bBardxtIW4HSaRRhXf6uRKLxVzNajQaSCQSNJtNPv8G6QR0ZkGQZKpI/svv9z+1BkFBsFarYW9vD/fv38fOzg5/acD3X7DNZsPc3Bzm5+exsrLCosdCb6rj42Nuh5Jtz3k92EIKttPpZAYXtWTIOkcYBE+LfdPPIWUYWoinIDjsdujpF5ICoNlsRq1WY1ZdOBzmLG8UDpKXAWXVtAtWKBSg0+mQSCRgsVjQbrdht9uh0WigUChOaNcS6YlUMOjntVot5PN5lMvlkUwGJBIJTCYTvF4vrl69CqfTeWIlqVAo8PUTsWJUqqPTkEqlmJycZMcSSrQvXbrE75EQlCTTPSoUCmyFRfZtL7vqdZ4gQQetVguLxYKpqSnelaOZtNFohFgsxvT0NBQKBdRqNYDvzyTgOzH7fD7PLi7neRYSIcbn88Hj8cBoNHJ7uVQq8ftAZJ9ntURJeYrEQiYmJtBut/n8G6QrxpkEQaEj/Kefforl5WXeQ6KNf9rNiUQi2NnZwc2bN9mnjb4gaj/RS/vuu+8iGAzCarXyzwK+e8CLxSKy2Szv+JynWDPNAGnu95d/+Zfwer1YWVkB8J0GYiKRQDKZxP3795FIJJhN6PF4TvwskUiEYDAIp9N5Qrh42JBIJJiZmYHL5cLPfvYzzMzMYHl5GXK5HNlsFl9++SX29/dxcHCAfD4/EruArwpii1JmSgejUqnExsYGt949Hg+mp6dZ+ULoTqJWqzE9Pc2KSZlMBkdHR4jH4yPj50YQigG43W4WiqZk6969e9jd3UUymWTW4ShBOKMl7dfPPvsMHo8H165dg16vf659mlB15fLly1CpVFhcXMTOzg4KhQILcGQymaGtvYjFYiae/exnP8P8/Dz7tJLJgEajYfWVdrvNvInJyUkoFAr4/X6WkqM2MXU6zprwI1wrcrlcbH5gMBjQaDQglUrhcDggEn1nBEw6tIVCAbFY7IS9GBVNVMX3ej0mOdKu8aDwxkFQuOBJsjlUvgvV+mkZl/awSElAeJhSFWK1WjE1NQWHw3FCVYa+wMPDQ5TLZaRSKZTL5RPO1+cBWmkwGAxwOBwIBAKYnp6GyWRCo9FAsVhkybBSqcQapxqNhithYaCjnj55II4CJiYmYDab4XA42BnCYDBwi2J/fx/b29sol8tvhWP680BEln6/zzuNUqkU1WoVOp2OlURImIHaNjKZjLVH1Wo1HwQ2m+1EC2hUAgnN54klSQvjtJTebDZ59kIrOaMEIidJpVLIZDJesVpcXITb7UYgEHihd6hQJcdqteLw8JCTgHw+z4vcZPb6LHHn84Zw9DM1NQW73X5CQJycZSQSCStoFQoFhMNh6HQ6Fp2mn0UkqPOSW6TfYTAYYDabYbPZoNfreZdYLpfDbDYzua7ZbDLxr1qtsvl0p9Pha6WAf3h4iEajgVqthkqlMtCk5I2DIH0p7777Lq5cuYLV1VXecaGWA2ne7ezs4Ouvv8bf//3fs0KD8MNarVb85je/werqKrdviHVErVTSznv48CHu3LmDR48esankeR1ARKH/5JNPcOHCBSwvL8NgMGBychLZbBYPHz7kqsLhcMDlcsFkMkGv1+PKlStPCTcrFAoOkkJCxrBAh2UgEEAwGMTS0hK3XBKJBCKRCJMn6GF+GwMggQIB7ZmKRCLU63Xk83lks1ns7u7i9u3b+Oqrr2CxWPDJJ5+w1yW1sYm999lnn8Hr9aLVaiGZTHLLbdi6kw6HA3a7HZcvX8bs7CyzYHu9HpMPNjc3EQqFUC6Xh7KO8yIQcczn88HhcOBnP/sZPB4PV3Uve8iTML1Op0O328XFixfRbreZePH48WPcv38fX3/9NRqNxsA6HHSfzGYzi3w7HI4TM03iUezt7SEej+Mf//EfUa/X0W63sbi4iOXlZR4jUWv3POUWJRIJNBoN/uIv/oL5ApRcuVwuJiuR9yYRXSKRCNbW1piUdnBwgH6/D5vNxp2WcrmMvb09bG1t4cmTJwMVs3/tIEitCrIgoYeVXJrJofr4+JhnMMlkEul0Gvl8Hs1mE8fHx9yfV6vVPE8k7T/6OQCYKlwulxEOh1lEtlKpnPuiq7DapRaMTCbjeZFWq+VdH6oYzGYz9Ho9PB4PB0G6PqER6LBtoEQiEbRaLYxGIxvOKpVKAOB2EfmWUYb2NgdAIYSat9RlEMqt0bDf7Xbj6OgIdrsdvV7vhPej1WpFp9OBxWJBq9VCuVweajVIi/EGgwEWi+Upclqv10O1WkWxWESlUuEVl2HPxk6D/CqpNU2dIVp/APDUvRP+s9OQSCT8h4QCyKosnU5DrVafILOd9zNODHGdTgeDwcAeogSaCTabTVZfoZYisZmpi0QekLVajcXIz+P66cynlTdKGoghLnyGKLkn+bq5uTnehZyYmMDR0REsFgurFnW7XdTrddTrdY4Ng8JrB0FqtzgcDiwsLODP/uzPeOmRGI/Ebnry5Ami0Si+/PJLbG5uolAo8MFPLcMrV64gGAzi+vXr3AYl0sjx8TGrPWxtbeG3v/0tIpEIDg4OuJVz3l8aBS26uRS87HY7fvWrX/EBSp9rYmKCB8PCvUbhASkMgEJR4EGBPs/S0hK8Xi+uXbvG89d8Po9QKISvv/4aDx48QCQSQblcHti1DRpC7VqaZSQSCchkMrRaLXi9XqjVarjdbm6PSiQSBAIBGAwGXLx4ESqVCslk8tydsF8EuVwOtVqN+fl5BAIBvP/++7xb1u12cXR0xBk3OSaMWmUvFotht9tx7do1XLt2DXNzc/D5fKwqIuycUIeIqo/nJSBCkhO1V2lFqVqtYnNzE9FoFAB4vHKe34nBYIDJZMLc3ByCwSAcDgd7I1JVd3BwgEQigb/7u79DIpFAOByGzWbD4uIir42JRCKUSiXs7Oxge3sb6XSa3dvPkxjTbDZx69YtNBoNFAoFFv2nypvUelwuF3Q6HX75y1+yOhhVenNzc7zy1m63USgUODF7K4KgVCo9oftms9mg1WohlUq5LM9kMigWi6wtGY/HUa1WT1RNpEKysrICj8cDk8nEmdrptYpMJoNkMoloNIpcLsduxeededPhWC6X+fdSlUpsT+HQt9frseJLqVTih5H+HfXtrVYrr0uQwLFarebF1/MGzTqFFbhGo+H9sYODA0SjUSSTyZHeHztr0P2i4JDJZCCXy1EqldiOh7JiEhafnp5mgW5K3IYBcl83mUwwm81MviJ2bL1eRzQaRSgU4md01AIgraTQ9VP3RSqVsqB5s9lEu91Gs9lklSaqIJ71eajjROfL1NQUq5ZMT0/j6tWrUCgUfE61Wq1ze+bJdYFEQKxWK8/GqOPVarUQCoWwt7eHWCyGUqnEDFI6JxUKBX/u3d1dHBwcoNVqnVtSQ3yMvb095HI5rlapnd7tdlkGMpVKQalUIpVKQa/XsxA4JSHUWiVRA+DZDkWDwGsHQVKhWF1dxeLiIjweD3/IarWKRqOB/f19JJNJ3L59G6lUCjs7O2i1Wtxa1Gq1uH79OjuUG41G/rJOq8uUy2UWNt7e3uaHdBAvMFWiyWQSWq0WlUqFW2JCdRGSaCLtvEKhgLW1Nc4qqe1kNpuh1Wrxzjvv8GCZdqBI8DccDp/756JK1efzYWlpCT6fDwC4/fLgwQNsbm5if39/pA7KQYFe+lgshm63i0wmA5PJdKLiJ3r3ysoK0/jb7fbQ9jyVSiWblBJxh9pP5XIZ2WwWjx8/xsOHD1EqlUYuuRF6j9L1m0wm/p6r1SqzsQuFAjKZDA4ODpDNZpHP559L8JHJZJDJZJidneW2KpFLlpeXodPpoNfr8eTJE65Kzms+KBKJYLFY4PP52JWFkmpidhYKBdy/fx8PHjzA1tYWAODSpUvw+/1YWlqC3W6HWq1m78dbt26dMNk9D9Ba0I0bNyCVSvmsI+cN4foJnY96vR56vR4ulwtut/uE8hexWumeDcsI4Y0qQYVCwS1QCgQAkMlkkEgksLa2hkQiwYSK4+NjfrjJ5+v69etwu93weDxMlyVJp3K5jEajgd3dXWSzWTx48AAHBwdcAQ7qy+p2u6yx2Gq1mHJ++fJlAN9RzqvVKmt/NhoNrnojkQhnp/SgWCwWVoig7FQ4czSZTM902D4vEA2dlqhpJzCTybBY9E8RQkq41WrlnSZhy5paynSgDpPkRGxIOng0Gg3fU/J229nZQSQSQTqd5jbiKIFaycViEVtbW+h0OohEIkyGqdVqaDQaSKfT3Jmhtu6LZtYkdEG+iW63G263G6urqzynstvtSKfTJ1xqzhoajQZ6vR4zMzMckGkPUHiftre3WceVZocrKyvMSu92u0gkEkxuOjg4QCaTOdcqipL8dDrNu830z6j9SueIRCLBxMQESqUSlEolMpkM4vE4zGYz75AT85/ep2GdM68VBIV0XHJ2oBkYABSLRUSj0RNtUGKfkfXG0tISpqamsLy8DJvNxgcIDUkpcy0UCtje3kYqleL/HXT2SgdFIpFArVaDRqNBNpuFw+Fge5ZMJsN7i5VKBYlEAs1mE4VCgR9MynKsVivMZjNKpRIvxp5uh9IS7KBAMxPh0n65XB456vyb4Hnz1me9fPSMS6VSGI1Grt5PGzkL3TbohR4G0UlIVCNxZboecr/I5XI4ODhgfdtRa4UC38/DKpUKwuEwms0m4vE4k0DI2YOWs4vFIgqFAgfH5wV1SlaA7wx6w+Ewcw5Iw9dgMLAotZCleZYgMpXb7cbU1BQ/V5Ss0CrE9vY2wuEwUqkU3G43zGYzZmZm4HQ6odFoUC6XUSwWWaQ6kUg8U6z/rEEJysuC2tvkNKPX67k1f+nSJRYgIQzjeXzlk5ZeNqlUym4IwkV2AIjH41hfX8fjx4/ZVZgcCZaXl3H16lWsrKycsFai9ufh4SG3OdbW1hAKhXDz5k3O+IbRvqGZIM0e+v0+Dg4OeLeIAgY5kjebTVQqFd6LAU7eXGGbl5ID4XcqZMWeJ6jCpeBdLBYhkUh4V9Pj8XC2/SoPp9CKif4MuuqguTMJOZAe7ekgRdksBQQiT1BrU6FQ4Je//CWmp6exsrICvV5/4ve02200Gg08evQI29vbQxMRoIA9PT3NZAu73c7yYDRrGnVlGBobpFIpNJtNJlrQ+0CzJ+oGUev5WdJcBGFCQ21RqlTo95H5crFYZIblecBms+HixYtYWlrC3NwczzuFYiKPHz/GjRs3WOj9gw8+gMfjwezsLCQSCbLZLHZ2drCzs4Nbt24hGo0+17l92KCzk3gihUIBMpmMmf7k5DJMvFEQFGpgCtFqtVCpVDhrE4lErGbgdrsRDAZ5pQL4PkDQ7K1cLiORSODg4AC7u7sIhULsUDyszJUIOjTva7Va2Nzc5OEwUZTJnZoWyp+FVqvFA2zhIF/okTaIaoJaT7Qs3Ol0uKWm1Wp5+E6tj5f57un5IPYwBR/K8Ad1/+iZI6ktst4RdiwA8D2g5IbULlQqFSYnJ6FUKjE7Owu3283fB/B9InN4eIhWq4V0Oo10Oj20FRI66DUaDYxGI1c1wlYT7W6NwmEpfL5Pf1+UIB4dHXESJVSLooP1ZVi49CzSfieJByiVSsjlck68iZ5fq9VYVeg87qNSqTxB+CFiSKfTQavV4kBMSkZkgeVyuaDRaNDpdNh0PBKJsAfkqLW1hRC2TUkajZIx4ff81rRD6XAzGo2w2Wxs+yF8UEmqibQWaQfw+vXruHTpEq5fv/7UzIsOolAohHv37uGrr77CgwcP2OV6VLQZSZSXqMHA9weicLD7omsVvsjCB4HYmqRVSbuW5wUKTNT+pMzb6/VyWzqXyyGZTKLVajEFXfjZKOgJ/5c8+sxmM89Atra2EI/HBzLLpSRtYWGBZeDsdjtmZ2e5uqPPXy6XUa/Xsbu7i+PjY0gkErjdbni9Xr4HVEkK1X2oZU8yT9988w329/f5WR00qK1kNBphtVrZJkoYbKgtOqhduOeBqjI6M8iAWghKMAin50Yvm5CRZ53L5YLZbGZnm48++ojtsRKJBDY2NrC+vo7t7W3u5pzH9zM5OckJCqnD0O4mVXjNZhMWiwUffPAB/H4/Lly4gMnJSV48/+abb7C1tYWtrS0UCgX2UX1bQAxmYlKfPjsHjVcOgnRQk+M4yeII20w6nY7lxcgE0mq1IhAIwGaz8TI2vYiUjVUqFYRCIYTDYV7QPm9niNeBMLN53b9PWbkw66QqUNiuGcSDUa/XWfiW5rwqlQoulwvBYJBnniShRtd0Osum9qNCoYBCoWBVFaKeE/ttEEGQdCMpoNlsNrhcLr5W4LvnT6VSMbWe2G0OhwNOp/NEYgfghA4uZbPRaBSJRALpdBqFQmGolaCwkyBUIqIqsF6vM+txWNdIwVq4BkUdoNMH+ekRwsv+DuIWkGiAy+XieVogEIDVaoVWq+W2XD6fx/7+PpNtztPBgCp2ukYhiBfgdDohlUoRCATY3eRZesmjbuX1PNDYR7hORHueb0UQJFYo7bjo9XqW2CIsLCzAbrfj6tWr6PV6MJlM0Gg0fLAIcXx8zPO2nZ0d/N//+3+xv7+Pra2tkRzcnwWOjo649VEqldhDkUgNwkzxvFvA/X4f4XAYrVaLlTno91+7dg1utxv/5t/8G/zxj39k70ZSU6EWo8fjOcH2omu3Wq2oVqvI5/OIx+O8anDeVYhYLIZcLselS5ewuLiI1dVVqNVqqNXqp9rMlMgJ9/+oBfes74p2P0OhEPb39/Htt99if38fDx48eEoGcBh4Vhv96OgI9Xode3t7uHnz5tDMZGnebDQa4XK5+BB8/Pgxvwdv8lzQfaMRjU6nw9zcHC5duoRr164hEAiwQDW15shs+a//+q8Rj8fZxmeQgUU4Lrpw4QK0Wi17JEokEl5tuXPnDvb29rC2toZisfjWileQQhXtR5OPLLXAB41XDoJUqRAD7bQ4NGXXdGMBsNSRcAGeWojJZBLlchmbm5vY29tDNBplm563LcN5WZCIbLVaRbVaRavVYnYhzeNoXeS8zT/7/T6q1SrEYjE2NjZQKpUgkUjYMVoikcDhcDCL12Kx8CFBGZ3ZbOYVAdofOjw8RCgUQi6Xe6ZY+iAgnLWefk4JRBwRUuKFXQ1qGVMlVS6XcXBwgL29PWxvb2Nvbw+pVGokvfhojl2r1ZDNZllsflijBaVSifn5eUxNTWFhYYHfg3q9DplMxl6Prwq6vzTHpeTc7/fD7/djcXGRkzvy/CR1knA4jHA4zISYQRjSPuv6qTvR6/X4LACATqeD3d1dxGIxbG9vIx6PcwX4tkIoUUgrWbRiNgwN29cKgpOTkzAajTCZTCcyZnqxtFrtierwWbRxaisRFfgf/uEfkE6nsbu7O5L7S2cJUq7P5/MwGo18CJAOKwUVlUrFc8fzRLFY5AfQYDAgmUwiEAiw+LLb7YZWq+XrpkOCAgvppVJrg3QOibm2s7ODcrk80HkZsf5elFlSQvZDknVUucdiMcRiMXz77bcs9FupVNButwcm3PAqIKPmYrGISCTCmr3DglarxXvvvYcLFy7g448/Rj6f5/0+uVyOZDL5yu+9cI5uMBig0+lw4cIFTE1N4cMPP4TD4YDH4+HdP5p90/rB3bt38ejRI2QymaGdO2QrRPuABDLZvnnzJvb29nDr1i1UKhUUi8WRe9ZeBZRUUgygNZdCoTAU9v8rB8F2u41qtYpwOAyJRIJSqcSMOqEOprDffXo4T/5ruVwOX3zxBcLhMPb29phZOWoZ9XlglB5iqgyECiLUqo1Go3C73cxkI7aoSCRCp9PhSqPZbPL9SyQSyGazePLkCbtrDLIKpJfr0aNHqFarLA03NzcHhUJxYibdbrdxeHjInpS1Wu2pWVSxWES9Xmdlko2NDd61o4Nz2F0LYkoSy5Ao86SBure3h1KpNNRrpGqN1KKIJU1z2pcRGqCzRLhS5Pf7YbPZsLCwALPZjLm5ORiNRkxPTzNngdqfe3t7SKfT+P3vf89qM+RCM4hzJ5/P48mTJ7BarSck4kQiEQthZ7NZpNNpJBIJ5PN5fPPNN2zT1m63h/6svSno+Tw8PDw3UYJXwSsHQRIYTqVSUCgULCFGD7HwIQWeHm5TVp1MJhEKhbC2tsYKFoeHhyMn5vtTABF9hCr01KqtVCpIp9MIBoMwGAywWq08yyGlnGQyybTter3OBINwOIxGo4F6vT7wz9PtdnmX02AwoFarwWq1otfrMTOZ1lsajQZisRj7XZ7+WalUij0VKTEgB+xReVaFKxtEQz86OmIyRTweR61WG+o1ktYqraDQ7E6hUPBurNBt5Xk/g6o/Yp77/X4Eg0FcvXoVNpsNPp+PyVkEWgOKRCIIh8P46quvkM/nkcvlBmqqWy6XEQqFEAgEoFar4XA4mNBEHof7+/vY3NzEzs4OM0Zp/erHUCAcHh7y+EDIpn9rViRoVheNRtFsNvFXf/VXCAQC+MUvfsHKC6dnKvV6Ha1WC4VCAeVyGfl8Hvfv32eBWCHN923Pct5mUEVYrVbRbrdRqVSQy+Wg0+mwsbHBdHNiTXY6HVbFoTYNLY/TzHMYLy2tn8RiMa7WLBYL9vf3mSADfPdskhBzMplkMebTiVupVOLnlwLMqFlKURW4t7fH+6wSiYRJSRsbGwNprb8M6HzQ6/WQyWT47LPPMDc3x4nY875XsVjMRDyPx8NJGVnyWCwWJpcdHR0hmUxyJUxKOeRiQ6tXg066S6USv2dra2v413/9V0xOTvKskhxMMpkMs+PL5TK39kfpmXsdiEQiOBwOeL1eFp7IZrPIZDLMQB80XjkI0jCzXq9DJBJhe3sbALC6ugqNRoPDw8MTFWGv10OlUuHqsVAoIJvNsh8gEUNGZQ9wmHjWvuGgQb+bsmMaXHc6HT5gKAiS0gbZn5DhLmV5wxKRBr77LhuNBrfeiWB0ukKgdmg+n+dW/+mfQ24LxP4c5ud6HoSamyRpKBaLOZEpFApotVrDvswTzzd5+rlcLshkMgQCgRcGQdJx1el0mJmZ4SBIYs00lyYfvnQ6zSau29vbSCQSCIVCLMJNlcggQckhOUPkcjnurNAep5AoQiOHYZ0H5wFikMtkMlatons2jJnsawVBOhja7TZu3LiBg4MDFItFnrecDoKNRoPpyPV6HZVKBalUCuVymQ+WH8sNfl2QbiDpIdKcbVjfS6/X44qCDlLhQjzw/bMgPNiE/3zYoCAej8eRTCaxs7PzTDazUM3mWYfiae3XUQS1Qre2trC7u4vbt2/zDp5QumqY6Ha73DEoFAosiUYi0v/+3//7F1Y7pI0qNGeVSCR8piQSCRatr1Qq3Amgqopa/PRcDAM08mm1Wk+xloVtwZcV3ngbIZPJMDk5CYlEwhJ4jUaDk9ZB47VVmoWtM6oIaWH6dDuUsm0KnGSNNEy69qiB5MtqtRrK5fK5OkS/CigADPsAfV3QojiAodCvB41R/oyksJNKpRAOh6HValnKDgAsFsszn3fazxQGBiL+UPVLwgUkuFGtVtlgtlwuc8dpFFavhM/kTxG0QiVUyhJa0g0arx0EKXumsj2RSLzwA5yeswz7cB81kHRZKBTC5uYmstnsue8IjjHGIFGv13Hv3j1mP9psNnZY12q1uHz58lNi/MB350UqlUKtVmMJP/IsrVQqiMfjTHIh822aTVP7epxsjwb6/T4qlQq35/v9PtRqNTQaDdRqNesuDxJn4tczDmqvjl6vx47la2trEIvFODo6wubmJiKRCBqNxvjFHeNHhcPDQ2SzWa7gMpkMK8hotVpWo3pWEEwmk6jVaojFYhwEScZPOFqh2e3R0RFXj+P3aLRAMo31ep3lIUmEZRDuOacxWNO6MRjHx8cIh8NMKqH1kWQyiXQ6jUql8ta2IMcY41k4PDxkR/hEIsFMT5Lpq9frHARP211REIzH4+zaQmQKYlGO8XagVCqxghFJp5FYyKB9VAFA9KIMSSQSjdOncwJRxOVyOTQaDYDvSUSko/dTnhuM8eOF0NuPFt5lMhksFgsfgqfJS0SaIFbn0dERiy7TqsMYbwcMBgPUajXm5+chkUjQbDZRLBaRSqWYN3LW6Pf7z53VjYPgGGOMMcYYP2q8KAj+sE7RGGOMMcYYY/xIMQ6CY4wxxhhj/GTxwnboGGOMMcYYY/yYMa4ExxhjjDHG+MliHATHGGOMMcb4yWIcBMcYY4wxxvjJYhwExxhjjDHG+MliHATHGGOMMcb4yWIcBMcYY4wxxvjJ4v8DEmTQmGnK4bUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import torchvision.utils as vutils\n",
    "\n",
    "real_batch = next(iter(train_loader))\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.axis(\"off\")\n",
    "plt.title(\"Training images\")\n",
    "plt.imshow(\n",
    "    np.transpose(\n",
    "        vutils.make_grid(real_batch[0][:64], padding=2, normalize=True), (1, 2, 0)\n",
    "    )\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "\n",
    "class PyTorchCNN(torch.nn.Module):\n",
    "    def __init__(self, num_classes):\n",
    "        super().__init__()\n",
    "\n",
    "        self.num_classes = num_classes\n",
    "        self.features = torch.nn.Sequential(\n",
    "            torch.nn.Conv2d(\n",
    "                in_channels=3,\n",
    "                out_channels=8,\n",
    "                kernel_size=(3, 3),\n",
    "                stride=(1, 1),\n",
    "                padding=1,\n",
    "            ),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2), padding=0),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.Conv2d(\n",
    "                in_channels=8,\n",
    "                out_channels=16,\n",
    "                kernel_size=(3, 3),\n",
    "                stride=(1, 1),\n",
    "                padding=1,\n",
    "            ),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2), padding=0),\n",
    "        )\n",
    "\n",
    "        self.classifier = torch.nn.Sequential(\n",
    "            torch.nn.Flatten(),\n",
    "            torch.nn.Linear(784, 128),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.Linear(128, num_classes),\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.features(x)\n",
    "        x = self.classifier(x)\n",
    "        return x\n",
    "\n",
    "\n",
    "torch.manual_seed(random_seed)\n",
    "model = PyTorchCNN(num_classes=num_classes)\n",
    "model = model.to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_accuracy(model, data_loader, device):\n",
    "    with torch.no_grad():\n",
    "        correct_pred, num_examples = 0, 0\n",
    "        for features, targets in data_loader:\n",
    "            features, targets = features.to(device), targets.to(device)\n",
    "            logits = model(features)\n",
    "            _, predicted_labels = torch.max(logits, 1)\n",
    "            num_examples += targets.size(0)\n",
    "            correct_pred += (predicted_labels == targets).sum()\n",
    "        return correct_pred.float() / num_examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 001/010 | Batch: 100/429 | Loss: 0.5552\n",
      "Epoch: 001/010 | Batch: 200/429 | Loss: 0.2319\n",
      "Epoch: 001/010 | Batch: 300/429 | Loss: 0.2143\n",
      "Epoch: 001/010 | Batch: 400/429 | Loss: 0.0994\n",
      "Training accuracy: 94.31% | Validation accuracy: 94.54%\n",
      "Time elapsed: 0.35 min\n",
      "Epoch: 002/010 | Batch: 100/429 | Loss: 0.1547\n",
      "Epoch: 002/010 | Batch: 200/429 | Loss: 0.1337\n",
      "Epoch: 002/010 | Batch: 300/429 | Loss: 0.1000\n",
      "Epoch: 002/010 | Batch: 400/429 | Loss: 0.0994\n",
      "Training accuracy: 97.23% | Validation accuracy: 97.30%\n",
      "Time elapsed: 0.71 min\n",
      "Epoch: 003/010 | Batch: 100/429 | Loss: 0.0571\n",
      "Epoch: 003/010 | Batch: 200/429 | Loss: 0.0435\n",
      "Epoch: 003/010 | Batch: 300/429 | Loss: 0.0878\n",
      "Epoch: 003/010 | Batch: 400/429 | Loss: 0.0801\n",
      "Training accuracy: 97.49% | Validation accuracy: 97.58%\n",
      "Time elapsed: 1.06 min\n",
      "Epoch: 004/010 | Batch: 100/429 | Loss: 0.0970\n",
      "Epoch: 004/010 | Batch: 200/429 | Loss: 0.0683\n",
      "Epoch: 004/010 | Batch: 300/429 | Loss: 0.1192\n",
      "Epoch: 004/010 | Batch: 400/429 | Loss: 0.0644\n",
      "Training accuracy: 98.24% | Validation accuracy: 98.28%\n",
      "Time elapsed: 1.41 min\n",
      "Epoch: 005/010 | Batch: 100/429 | Loss: 0.0628\n",
      "Epoch: 005/010 | Batch: 200/429 | Loss: 0.0466\n",
      "Epoch: 005/010 | Batch: 300/429 | Loss: 0.0534\n",
      "Epoch: 005/010 | Batch: 400/429 | Loss: 0.0801\n",
      "Training accuracy: 98.51% | Validation accuracy: 98.18%\n",
      "Time elapsed: 1.77 min\n",
      "Epoch: 006/010 | Batch: 100/429 | Loss: 0.0650\n",
      "Epoch: 006/010 | Batch: 200/429 | Loss: 0.0892\n",
      "Epoch: 006/010 | Batch: 300/429 | Loss: 0.0580\n",
      "Epoch: 006/010 | Batch: 400/429 | Loss: 0.0695\n",
      "Training accuracy: 98.68% | Validation accuracy: 98.42%\n",
      "Time elapsed: 2.12 min\n",
      "Epoch: 007/010 | Batch: 100/429 | Loss: 0.0268\n",
      "Epoch: 007/010 | Batch: 200/429 | Loss: 0.0201\n",
      "Epoch: 007/010 | Batch: 300/429 | Loss: 0.0507\n",
      "Epoch: 007/010 | Batch: 400/429 | Loss: 0.1108\n",
      "Training accuracy: 98.89% | Validation accuracy: 98.62%\n",
      "Time elapsed: 2.47 min\n",
      "Epoch: 008/010 | Batch: 100/429 | Loss: 0.0170\n",
      "Epoch: 008/010 | Batch: 200/429 | Loss: 0.0484\n",
      "Epoch: 008/010 | Batch: 300/429 | Loss: 0.0277\n",
      "Epoch: 008/010 | Batch: 400/429 | Loss: 0.0154\n",
      "Training accuracy: 98.83% | Validation accuracy: 98.76%\n",
      "Time elapsed: 2.82 min\n",
      "Epoch: 009/010 | Batch: 100/429 | Loss: 0.0489\n",
      "Epoch: 009/010 | Batch: 200/429 | Loss: 0.0467\n",
      "Epoch: 009/010 | Batch: 300/429 | Loss: 0.0424\n",
      "Epoch: 009/010 | Batch: 400/429 | Loss: 0.0447\n",
      "Training accuracy: 98.89% | Validation accuracy: 98.60%\n",
      "Time elapsed: 3.18 min\n",
      "Epoch: 010/010 | Batch: 100/429 | Loss: 0.0254\n",
      "Epoch: 010/010 | Batch: 200/429 | Loss: 0.0279\n",
      "Epoch: 010/010 | Batch: 300/429 | Loss: 0.1073\n",
      "Epoch: 010/010 | Batch: 400/429 | Loss: 0.0370\n",
      "Training accuracy: 99.02% | Validation accuracy: 98.70%\n",
      "Time elapsed: 3.53 min\n",
      "Total training time: 3.53 min\n"
     ]
    }
   ],
   "source": [
    "optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)\n",
    "\n",
    "start_time = time.time()\n",
    "for epoch in range(num_epochs):\n",
    "    model = model.train()\n",
    "    for batch_idx, (features, targets) in enumerate(train_loader):\n",
    "\n",
    "        features, targets = features.to(device), targets.to(device)\n",
    "\n",
    "        ### Forward pass\n",
    "        logits = model(features)\n",
    "        loss = F.cross_entropy(logits, targets)\n",
    "\n",
    "        ### Backward pass (backpropagation)\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "\n",
    "        ### Update model parameters\n",
    "        optimizer.step()\n",
    "\n",
    "        ### Batch-level logging\n",
    "        if not (batch_idx + 1) % 100:\n",
    "            print(\n",
    "                f\"Epoch: {epoch + 1:03d}/{num_epochs:03d} | \"\n",
    "                f\"Batch: {batch_idx + 1:03d}/{len(train_loader):03d} | \"\n",
    "                f\"Loss: {loss:.4f}\"\n",
    "            )\n",
    "\n",
    "    ### Epoch-level logging\n",
    "    model = model.eval()\n",
    "    train_acc = compute_accuracy(model, train_loader, device)\n",
    "    valid_acc = compute_accuracy(model, valid_loader, device)\n",
    "    print(\n",
    "        f\"Training accuracy: {train_acc * 100:.2f}% | \"\n",
    "        f\"Validation accuracy: {valid_acc * 100:.2f}%\"\n",
    "    )\n",
    "    print(f\"Time elapsed: {(time.time() - start_time) / 60:.2f} min\")\n",
    "\n",
    "print(f\"Total training time: {(time.time() - start_time) / 60:.2f} min\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test accuracy: 99.14%\n"
     ]
    }
   ],
   "source": [
    "test_acc = compute_accuracy(model, test_loader, device)\n",
    "print(f\"Test accuracy: {test_acc*100:.2f}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy      : 1.19.5\n",
      "torch      : 1.11.0\n",
      "matplotlib : 3.3.4\n",
      "torchvision: 0.12.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%watermark -iv"
   ]
  }
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